担当区分：筆頭著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

In the phenomenon of stochastic resonance, adding a certain level of nonzero noise to a nonlinear system reduces information loss. A previous study proposed a neural network consisting of thresholding functions that exploit stochastic resonance at run time and during training, with the aim of smooth mapping and backpropagation. Such a neural network can be rephrased as one that operates only when noise is added, i.e., one that is unable to smoothly map and train when noise is absent. Focusing on both explanations simultaneously, a neural network for which only a sub-network is activated selectively by adding noise locally on that sub-network is proposed in this paper. To this end, a new activation function is introduced. It exploits stochastic resonance and presents null output and derivative when no noise is added. Simple simulations confirm that the proposed neural network with the new activation function allows the sub-network to be functionalized selectively, and interpolations are investigated by imposing varying noise intensity on various regions of the network after sub-networks are trained separately.

DOI： 10.1016/j.neucom.2020.05.125

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担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

This study proposes a vacuum gripper that can measure the effective suction force applied to an object using a 6-axis force sensor. The object falling in a vacuum gripper occurs when a gap between the object and the pad no longer allows the negative pressure in the chamber. This is rephrased as the absence of a compression force between the object and the pad. Therefore, the force distribution that the attached object pushes the pad during suction reflects the external force, i.e. the effective suction force, required to remove the object. To confirm the validity of the developed vacuum gripper, we conducted an experiment where the developed vacuum gripper sucks a flat plate. As a result, we confirmed that the 6-axis force sensor’s signals mean the effective suction force by applying an external force to remove the place.

DOI： 10.1007/s10015-023-00935-2

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記述言語：英語   掲載種別：研究論文（学術雑誌）

The importance of haptic in-sensor computing devices has been increasing. Herein, a haptic sensor with a hierarchical structure is successfully fabricated via the sacrificial template method, using carbon nanotube-polydimethylsiloxane (CNT-PDMS) nanocomposites for in-sensor computing applications. The CNT-PDMS nanocomposite sensors, with different sensitivities, are obtained by varying the amount of CNTs. The input stimuli are transformed into higher-dimensional information, enabling a new path for the CNT-PDMS nanocomposite application, which is implemented on a robotic hand as an in-sensor computing device by applying a reservoir computing paradigm. The nonlinear output data obtained from the sensors are trained using linear regression and used to classify nine different objects used in everyday life with an object recognition accuracy of >80% for each object. This approach can enable tactile sensation in robots while reducing the computational cost.

DOI： 10.1002/aisy.202400640

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Musculoskeletal systems are characterized by their structural softness and drive redundancy. The objective of this study was to reproduce these features using a tensegrity manipulator. The developed tensegrity manipulator was formed by replacing 40 of the 80 cables of class-1 tensegrity consisting of 20 struts with pneumatic cylinders to allow it to bend actively. This paper presents the design details of the manipulator and an analysis of its characteristics during various motions. We confirmed that this robotic platform could reproduce abstract features of the musculoskeletal system. In addition, we discuss the issues that must be addressed in the control of this robot according to the experimental results.

DOI： 10.20965/jrm.2023.p1366

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担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： https://doi.org/10.20965/jrm.2023.p1366

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Differentiable Filters are recursive Bayesian estimators that derive the state transition and measurement models from data alone. Their data-driven nature eschews the need for explicit analytical models, while remaining algorithmic components of the filtering process intact. As a result, the gain mechanism - a critical component of the filtering process - remains non-differentiable and cannot be adjusted to the specific nature of the task or context. In this paper, we propose an attention-based Multimodal Differentiable Filter (α-MDF) which utilizes modern attention mechanisms to learn multimodal latent representations. Unlike previous differentiable filter frameworks, α-MDF substitutes the traditional gain, e.g., the Kalman gain, with a neural attention mechanism. The approach generates specialized, context-dependent gains that can effectively combine multiple input modalities and observed variables. We validate α-MDF on a diverse set of robot state estimation tasks in real world and simulation. Our results show α-MDF achieves significant reductions in state estimation errors, demonstrating nearly 4-fold improvements compared to state-of-the-art sensor fusion strategies for rigid body robots. Additionally, the α-MDF consistently outperforms differentiable filter baselines by up to 45% in soft robotics tasks. The project is available at alpha-mdf.github.io and the codebase is at github.com/ir-lab/alpha-MDF.

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担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

This paper uses a data-driven approach to model a highly redundantly driven tensegrity manipulator's forward and inverse kinematics. The tensegrity manipulator is based on a class-1 tensegrity with 20 struts and bends by 40 pneumatic actuators whose internal pressures are independently controlled. Based on the data obtained through random trials with the robot, a VAE-based kinematics model is trained. The forward model, inverse model, and null space of kinematics are simultaneously acquired as subnetworks of the VAE-based kinematics model. Experiments confirmed that the subnetworks representing forward and inverse kinematics could be used for the end position estimation and control, respectively. In addition, the subnetwork representing null space can generate different target pressures that achieve the same end position, which was confirmed to mean variable stiffness properties similar to musculoskeletal robots.

DOI： 10.1109/IROS55552.2023.10341525

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

This paper introduces a novel approach for modeling the dynamics of soft robots, utilizing a differentiable filter architecture. The proposed approach enables end-to-end training to learn system dynamics, noise characteristics, and temporal behavior of the robot. A novel spatio-temporal embedding process is discussed to handle observations with varying sensor placements and sampling frequencies. The efficacy of this approach is demonstrated on a tensegrity robot arm by learning end-effector dynamics from demonstrations with complex bending motions. The model is proven to be robust against missing modalities, diverse sensor placement, and varying sampling rates. Additionally, the proposed framework is shown to identify physical interactions with humans during motion. The utilization of a differentiable filter presents a novel solution to the difficulties of modeling soft robot dynamics. Our approach shows substantial improvement in accuracy compared to state-of-the-art filtering methods, with at least a 24% reduction in mean absolute error (MAE) observed. Furthermore, the predicted end-effector positions show an average MAE of 25.77mm from the ground truth, highlighting the advantage of our approach. The code is available at https://github.com/ir-lab/soft_robot_DEnKF.

DOI： 10.1109/IROS55552.2023.10341856

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Biological bodies have numerous redundant soft muscles. In our laboratory, we pursue both the softness and redundancy of biological bodies in robots. We propose the suitability of the “tensegrity” structure for enhancing softness and redundancy in robots. Tensegrity is a structure composed of struts and cables without strut connections. This structure is soft and contains numerous actuators. Herein, we develop a tensegrity manipulator driven by 20 pneumatic cylinders with 20 springs to enhance the softness and redundancy. The robot moves the changing tensile forces of its cables using pneumatic cylinders. The complex relationship between the actuator inputs and the robot’s postures to control this robot must be modeled. In this study, the forward kinematics is modeled by machine learning. The inverse kinematics is solved numerically by deriving the Jacobi matrix from the derived forward kinematic model. This study reports on this simple kinematic model and discusses ways to improve it.

DOI： 10.1007/s10015-022-00789-0

Kyutacar

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担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

担当区分：筆頭著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

Neural networks have been widely used to model nonlinear systems that are difficult to formulate. Thus far, because neural networks are a radically different approach to mathematical modeling, control theory has not been applied to them, even if they approximate the nonlinear state equation of a control object. In this research, we propose a new approach—i.e., neural model extraction, that enables model-based control for a feed-forward neural network trained for a nonlinear state equation. Specifically, we propose a method for extracting the linear state equations that are equivalent to the neural network corresponding to given input vectors. We conducted simple simulations of a two degrees-of-freedom planar manipulator to verify how the proposed method enables model-based control on neural network forward models. Through simulations, where different settings of the manipulator’s state observation are assumed, we successfully confirm the validity of the proposed method.

DOI： 10.1007/s42979-021-00456-4

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2020, Fuji Technology Press. All rights reserved. The Nakanoshima Challenge is a contest for developing sophisticated navigation systems of robots for col-lecting garbage in outdoor public spaces. In this study, a robot named Navit(oo)n is designed, and its perfor-mance in public spaces such as city parks is evaluated. Navit(oo)n contains two 2D LiDAR scanners with uniaxial gimbal mechanism, improving self-localization robustness on a slope. The gimbal mechanism adjusts the angle of the LiDAR scanner, preventing erroneous ground detection. We evaluate the navigation perfor-mance of Navit(oo)n in the Nakanoshima and its Extra Challenges.

DOI： 10.20965/jrm.2020.p1173

Kyutacar

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Imitation learning is an intuitive approach for teaching motion to robotic systems. Although previous studies have proposed various methods to model demonstrated movement primitives, one of the limitations of existing methods is that the shape of the trajectories is encoded in high dimensional space. The high dimensionality of the trajectory representation can be a bottleneck in the subsequent process such as planning a sequence of primitive motions. We address this problem by learning the latent space of the robot trajectory. If the latent variable of the trajectories can be learned, it can be used to tune the trajectory in an intuitive manner even when the user is not an expert. We propose a framework for modeling demonstrated trajectories with a neural network that learns the low-dimensional latent space. Our neural network structure is built on the variational autoencoder (VAE) with discrete and continuous latent variables. We extend the structure of the existing VAE to obtain the decoder that is conditioned on the goal position of the trajectory for generalization to different goal positions. Although the inference performed by VAE is not accurate, the positioning error at the generalized goal position can be reduced to less than 1 mm by incorporating the projection onto the solution space. To cope with requirement of the massive training data, we use a trajectory augmentation technique inspired by the data augmentation commonly used in the computer vision community. In the proposed framework, the latent variables that encodes the multiple types of trajectories are learned in an unsupervised manner, although existing methods usually require label information to model diverse behaviors. The learned decoder can be used as a motion planner in which the user can specify the goal position and the trajectory types by setting the latent variables. The experimental results show that our neural network can be trained using a limited number of demonstrated trajectories and that the interpretable latent representations can be learned.

DOI： 10.1007/s42979-020-00324-7

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group and The Robotics Society of Japan. Q-bot is the human-sized carriage robot for lifting heavy weight objects of in-house logistics, such as storehouse and convenience store. The main feature of Q-bot is the adhesion mechanism beneath the foot, called the turnover prevention Universal Vacuum Gripper (in short TP UVG) that holds its body for turnover prevention and self-weight compensation. Turnover prevention is one of the key technologies of in-house logistic robot for effective use of it. Self-weight compensation is another clue for the robot to achieve the labor work in narrow space. TP UVG is achieved both functions by adhering to uneven ground. The other function of Q-bot is multiple objects graspability based on two-sized Universal Vacuum Gripper by dual-armed manipulation. Q-bot also has omnidirectional movability based on mecanum wheels. In this research, we will report on the development of Q-bot and experiments to prevent the robot from falling when it grabs a heavy object while attached to the ground. We also report Q-bot demonstrations of Future Convenience-Store Challenge in the World Robot Summit 2018.

DOI： 10.1080/01691864.2019.1709987

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2019 IEEE. A spine of a quadruped animal has compliantly connected several segments. This structure enables the animal to realize bending/stretching motion during running along with the motion of the legs. In this paper, we describe a link mechanism for mimicking such bending/stretching motion of the spine and the leg with few degrees of freedom. By designing a linkage mechanism, we try to realize a similar motion of the spine and the hind leg as that of a cheetah. We developed a prototype with such a structure and demonstrate that it can realize the similar movement of the spine and the leg as that of a cheetah with a simple control strategy.

DOI： 10.1109/ROBIO49542.2019.8961719

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2019 IEEE. Motor babbling and goal babbling has been used for sensorimotor learning of highly redundant systems in soft robotics. Recent works in goal babbling have demonstrated successful learning of inverse kinematics (IK) on such systems, and suggest that babbling in the goal space better resolves motor redundancy by learning as few yet efficient sensorimotor mappings as possible. However, for musculoskeletal robot systems, motor redundancy can provide useful information to explain muscle activation patterns, thus the term motor abundance. In this work, we introduce some simple heuristics to empirically define the unknown goal space, and learn the IK of a 10 DoF musculoskeletal robot arm using directed goal babbling. We then further propose local online motor babbling guided by Covariance Matrix Adaptation Evolution Strategy (CMA-ES), which bootstraps on the goal babbling samples for initialization, such that motor abundance can be queried online for any static goal. Our approach leverages the resolving of redundancies and the efficient guided exploration of motor abundance in two stages of learning, allowing both kinematic accuracy and motor variability at the queried goal. The result shows that local online motor babbling guided by CMA-ES can efficiently explore motor abundance at queried goal positions on a musculoskeletal robot system and gives useful insights in terms of muscle stiffness and synergy.

DOI： 10.1109/IROS40897.2019.8967791

Kyutacar

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担当区分：最終著者,　責任著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2019 IEEE. It has been widely considered that a distinctive feature of musculoskeletal structures is that both the joint angle and stiffness can be changed by exploiting the agonistantagonist driving of the joint. However, musculoskeletal systems in animals and humans are typically highly complex, and the simple agonist-antagonist driving is rarely found. Therefore, in accordance with the increasing complexity of musculoskeletal robots, the feature that causes the robot to assume a posture with different stiffness values becomes difficult to achieve, owing to the difficulty in modeling the kinematics. Although datadriven approaches such as the neural network are regarded as suitable for modeling complex relationships, the training data are difficult to obtain because measuring joint stiffness is typically extremely difficult in contrast to measuring an actuator's state and posture. Hence, we herein propose the common dimensional autoencoder where the encoded feature exhibits identical dimensions to the original input vector. In the proposed network, in parallel with the original unsupervised training using the data of the actuators' states, supervised training at part of the encoded features is performed using posture data. Consequently, features expressing the redundancy of inverse kinematics appear at the remaining part of the encoded features without using data such as joint stiffness. The validity of the proposed method was confirmed successfully through an experiment using a 10 degrees-of-freedom complex musculoskeletal robot arm driven by pneumatic artificial muscles.

DOI： 10.1109/IROS40897.2019.8968605

Kyutacar

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2019 IEEE. Musculoskeletal robots that are based on pneumatic actuation have a variety of properties, such as compliance and back-drivability, that render them particularly appealing for human-robot collaboration. However, programming interactive and responsive behaviors for such systems is extremely challenging due to the nonlinearity and uncertainty inherent to their control. In this paper, we propose an approach for learning Bayesian Interaction Primitives for musculoskeletal robots given a limited set of example demonstrations. We show that this approach is capable of real-time state estimation and response generation for interaction with a robot for which no analytical model exists. Human-robot interaction experiments on a 'handshake' task show that the approach generalizes to new positions, interaction partners, and movement velocities.

DOI： 10.1109/IROS40897.2019.8967845

Kyutacar

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2019, Springer Nature Switzerland AG. Understanding of the design principles for implementing adaptive functions with respect to engineering currently remains stalled in the conceptual level. However, living organisms exhibit great adaptive function by skillfully relating shape and function in a spatio-temporal manner. In this study, we focus on amoeboid organisms because these organisms have a variable morphology that relates shape and function. Amoeboid organisms in the natural world (i.e., cellular slime molds) locomote through changing the cell membrane shape by inducing the internal protoplasmic streaming. Based on this mechanism, we developed modular robots that modeled the cell membrane dynamics of a cellar slime mold.

DOI： 10.1007/978-3-030-01370-7_24

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2019, Springer Nature Switzerland AG. In contrast with intensive studies for hardware development in soft robotics, approaches to construct a controller for soft robots has been relying on heuristics. One of the biggest reasons of this issue is that even reconstructing the state-space to describe the behavior is difficult. In this study, we propose a method to reconstruct state-space from movies using a convolutional autoencoder for robot control. In the proposed method, the process that reduces the number of dimensions of each frame in movies is regulated by additional losses making latent variables orthogonal each other and apt to model the forward dynamics. The proposed method was successfully validated through a simulation where a two links planar manipulator is modeled using the movie and controlled based on the forward model.

DOI： 10.1007/978-3-030-01370-7_38

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2019, Springer Nature Switzerland AG. One of the distinctive features of musculoskeletal systems is the redundancy provided by agonist-antagonist muscle pairs. To identify agonist-antagonist muscle pairs in a musculoskeletal robot, however, is difficult as it requires complex structures to mimic human physiology. Thus, we propose a method to identify agonist-antagonist muscle pairs in a complex musculoskeletal robot using motor commands. Moreover, the common dimensional autoencoder, where the encoded feature has identical dimensions to the original input vector, is used to separate the image and the kernel spaces for each time period. Finally, we successfully confirmed the efficacy of our method by applying a 2-link planar manipulator to a 3-pairs-6-muscles configuration.

DOI： 10.1007/978-3-030-01370-7_26

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2019, Springer Nature Switzerland AG. Pneumatic artificial muscles (PAMs) actuating bio-inspired structures are widely used to mimic the human musculoskeletal system. The research in this field can improve the understanding of the human’s physical abilities through a close recreation of its natural structure. This paper will introduce an enhancement to PAMs resembling the sensory-feedback of the muscles spindles’ group Ia and II afferent neurons. The artificial muscle spindle presented in this paper is embedded into the muscle and wraps around like its biological counterpart. Previous publications of artificial muscle spindles mostly aimed to output a signal, which correlates to the length of the muscle. This approach, however, aimed to recreate the natural muscle spindle as close as possible in regards to its functional principal and positioning inside of the PAM. By using conductive fabrics, a deeply embedded sensor type was created, which feedback correlates to the expansion of the PAM’s inner tube, as well as the pressure in-between of the inner tube and the outer braided sleeve. In this paper, a constructional approach on a biomimetic muscle spindle is introduced, including its Ia and II afferent neurons.

DOI： 10.1007/978-3-030-24741-6_15

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2018 IEEE. A number of researches have been focusing on the development and control of robots with soft structures such as flexible musculoskeletal systems. Thus far, it has been reported that these robots can achieve high adaptability to environments despite their extremely simple controllers. However, because these robots are difficult to model mathematically, there is still no systematic design policy, in which control theory has been playing a role in conventional robotics, for constituting simple controllers. To tackle this problem, we propose a new approach using a neural network to obtain mathematical models. In particular, with this method, the control theory is applied to linear system models extracted from a network trained to express the forward dynamics of a robot. Through simulations, the validity and advantage of the proposed method was successfully confirmed.

DOI： 10.1109/IROS.2018.8593507

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2018 Both scientists and roboticists widely agree that the musculoskeletal system of the human foot plays an important role in locomotion. Nevertheless, the contribution of the foot musculoskeletal system has not been fully uncovered because currently it is impossible to modify and evaluate musculoskeletons in living animals. Here, to understand the effects of foot windlass mechanism, we construct a bipedal robot, which has similar musculoskeleton and dynamics to those of human. By implementing experiments on this robot, we investigate the effects (e.g. jumping height) of foot windlass mechanism on drop jumping, a simple and representative bouncing gait comprising landing and push-off. Through a significant number of drop jumping trials, the results demonstrated that (1) the windlass mechanism is passively activated in the push-off phase and that (2) it contributes to the height of jumping. Our results suggest that the foot windlass mechanism contributes to the energy efficiency and performance in locomotion.

DOI： 10.1016/j.robot.2018.09.006

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2018 IEEE. In this paper we present an object manipulation experiment using our musculoskeletal humanoid robot. The robot has to turn a crank in this experiment. This tasks provides a good representation of real-world tasks humans solve every day, when operating mechanisms. With this experiment we could show that the humanoid bio-inspired and compliant design allows it to accomplish this task with a simple key frame based motion control.

DOI： 10.1109/MHS.2018.8886947

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2018, © 2018 Taylor & Francis and The Robotics Society of Japan. This paper describes the construction and design decisions of an anthropomorphic musculoskeletal robot arm actuated by pneumatic artificial muscles. This robot was designed to allow human-inspired compliant movements without the need to replicate the human body-structure in detail. This resulted in an mechanically simple design while preserving the motoric characteristics of a human. Besides the constructional details of the robot we will present two experiments to show the robots abilities regarding to its dexterity and compliance.

DOI： 10.1080/01691864.2018.1494040

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2018 IEEE. A new approach of controlling quadrupedal robots would be posed by the recent breakthroughs in machine learning. Considering that these techniques typically require many trials to figure out adequate control inputs, the design specialized for this purpose will benefit. In this study, we are trying to develop a new quadrupedal robot driven by pneumatic cylinders centrally mounted on the body for archiving the simplicity of the mechanical design and the ability of performing multiple gaits. In this paper, we demonstrate the design of the developed pneumatic quadrupedal robot and indicate the robot can perform multiple gaits.

DOI： 10.1109/ROBIO.2018.8664769

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2018 IEEE. Pneumatic system is playing an important role in the field of soft robotics. In this study, we propose new concept of pneumatic tactile sensing for handling with the limitation occurred when the spatial resolution is bounded by the size of single chamber. The new concept uses multiple pressure sensors installed into single chamber and exploits the difference of arrival times of a pressure wave. By using this concept, the spatial resolution is not principally bounded by the size of single chamber anymore. In this paper, the principle is explained and the validity is confirmed through experimental results.

DOI： 10.1109/ROBIO.2018.8665065

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2018 Taylor & Francis and The Robotics Society of Japan. Task performed at a height, such as wall inspections are one of the dangerous tasks for humans. Thus, robotic technology for safety inspection is required. This research focuses on developing robots to climb vertical walls with flat and uneven surfaces, e.g. concrete, tile and riveted structure. To have wall-climbing capability, climbing robots use vacuum pads, claws, magnets, intermolecular force, and adhesive. However, each of these approaches has disadvantages. To achieve wall climbing on an uneven surface without scratching and staining, we have developed a novel vacuum pad named the Universal Vacuum Gripper (UVG), which is based on the Universal Gripper (UG). The UG is a robot hand using jamming transition of coffee powder inside a balloon to grip uneven material. The UVG is a vacuum pad with a deformable skirt based on the UG. If the skirt shape is deformed in accordance with the contact surface, air leaks can be avoided. Moreover, the deformed skirt can be stiffened, thereby working as a gripper. Here, we evaluate the proposed gripper, having both grasping and adhesion force. We also develop a wall-climbing robot with UVGs, and evaluate its performance on uneven surfaces under real-world conditions.

DOI： 10.1080/01691864.2018.1447238

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2018 Taylor & Francis and The Robotics Society of Japan. Several factors affect the performance of humanoid walking. One factor is the complex nature of lower limbs, especially the muscles around the pelvis that contribute significantly to the stability and adaptivity of humanoid locomotion. The significance of this muscle group assures a impact on the facility of walking robots once the nature of its contribution is understood, and it can be replicated on robots. To propose a mechanical structure that facilitates walking in robots, we realized a muscle by modeling its pelvis region like that of a humanoid and developing a musculoskeletal humanoid robot. Especially, we focused on the gluteus medius, which is important for the general stability against frontal movements of the hip. Furthermore, it passively changes its influence on such motions; this is helpful during the different phases of locomotion. These changes depend on the alignment of the pelvis and femur. We confirmed the viability of the robotic gluteus medius, which was simplified to a model of two partial muscles by accomplishing the walking using this robot. This accomplishment verifies our hypothesis that using this model, the supporting functionality for the locomotion of the muscle can be reproduced and enhances the biological plausibility.

DOI： 10.1080/01691864.2018.1434015

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担当区分：筆頭著者,　責任著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2017 Elsevier B.V. Stochastic resonance (SR) is a phenomenon by which the input signal of a nonlinear system, with magnitude too small to affect the output, becomes observable by adding a non-zero level of noise to the system. SR is known to assist biological beings in coping with noisy environments, providing sophisticated information processing and adaptive behaviors. The SR effect can be interpreted as a decrease in the input-output information loss of a nonlinear system by making it stochastically closer to a linear system. This work shows how SR can improve the performance of a system even when the desired input-output relationship is nonlinear, specifically for the case of a neural networks whose hidden layers consist of threshold functions. Universal approximation capability of neural networks exploiting SR is then discussed: although a network consisting of threshold activation functions has been proven to be an universal approximator in the context of the extreme learning machine (ELM), once SR is taken into account, the system can be deemed as a classic three-layer neural network whose universality has been previously proven by simpler proofs. After proving the universal approximation capability for an infinite number of hidden units, the performance achieved with a finite number of hidden units is evaluated using two training algorithms, namely backpropagation and ELM. Results highlight the SR effect occurring in the proposed system, and the relationship among the number of hidden units, noise intensity, and approximation performance.

DOI： 10.1016/j.neucom.2016.12.111

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2018 The Author(s) Published by the Royal Society. All rights reserved. To maintain balance during dynamic locomotion, the effects of proprioceptive sensory feedback control (e.g. reflexive control) should not be ignored because of its simple sensation and fast reaction time. Scientists have identified the pathways of reflexes; however, it is difficult to investigate their effects during locomotion because locomotion is controlled by a complex neural system and current technology does not allow us to change the control pathways in living humans. To understand these effects, we construct a musculoskeletal bipedal robot, which has similar body structure and dynamics to those of a human. By conducting experiments on this robot, we investigate the effects of reflexes (stretch reflex and crossed inhibitory response) on posture during hopping, a simple and representative bouncing gait with complex dynamics. Through over 300 hopping trials, we confirm that both the stretch reflex and crossed response can contribute to reducing the lateral inclination during hopping. These reflexive pathways do not use any prior knowledge of the dynamic information of the body such as its inclination. Beyond improving the understanding of the human neural system, this study provides roboticists with biomimetic ideas for robot locomotion control.

DOI： 10.1098/rsif.2018.0024

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2017 The Authors. The anatomical design of the human foot is considered to facilitate generation of bipedal walking. However, how the morphology and structure of the human foot actually contribute to generation of bipedal walking remains unclear. In the present study, we investigated the three-dimensional kinematics of the foot bones under a weight-bearing condition using cadaver specimens, to characterize the innate mobility of the human foot inherently prescribed in its morphology and structure. Five cadaver feet were axially loaded up to 588N (60 kgf), and radiographic images were captured using a biplane X-ray fluoroscopy system. The present study demonstrated that the talus is medioinferiorly translated and internally rotated as the calcaneus is everted owing to axial loading, causing internal rotation of the tibia and flattening of the medial longitudinal arch in the foot. Furthermore, as the talus is internally rotated, the talar head moves medially with respect to the navicular, inducing external rotation of the navicular and metatarsals. Under axial loading, the cuboid is everted simultaneously with the calcaneus owing to the osseous locking mechanism in the calcaneocuboid joint. Such detailed descriptions about the innate mobility of the human foot will contribute to clarifying functional adaptation and pathogenic mechanisms of the human foot.

DOI： 10.1098/rsos.171086

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記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1080/19424280.2017.1314387

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2016 IEEE. Many mechanisms reduce the number of inputs for their target motions by restricting the motions of pairs of joints. This study designs a novel constraint mechanism using a pair of noncircular pulleys and a wire. The wire restricts the motion of the joints to the target motion while enabling a compact structure. We analytically derive the shape of the noncircular pulleys using the desired relation between the joints and the lengths of their moment arms. The usability of the proposed mechanism is evaluated on a robotic leg, which maintains the height and posture of its upper body under the constraints.

DOI： 10.1109/TMECH.2016.2614961

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2016 IEEE. Humans are supposed to use body image representation for realizing adaptive behavior in dynamically changing environment. This paper describes a newly developed muscular-skeletal humanoid robot with local reflexes for approaching how the body structure and the local reflexes contribute to constructing body image from the constructivist viewpoint. The muscular-skeletal humanoid has human-like bone structure with a number of muscles each of which is equipped with proprioceptive sensors.

DOI： 10.1109/MHS.2016.7824178

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© Springer International Publishing AG 2017. This paper presents a master–slave finger exoskeleton developed to allow subjects whose brain activity is being measured by functional magnetic resonance imaging (fMRI) to remotely perform tasks. The MRI environment requires the device to be free from metal components and strongly immobilized, which can reduce the device’s versatility and ease of setup. To overcome these limitations, we designed a finger exoskeleton using pneumatic artificial muscles, which can be made metal–free and used for not only actuators but also sensors. We also proposed a symmetric, bilateral control method for the device, and experimentally validated device performance and its control method.

DOI： 10.1007/978-3-319-48036-7_7

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2016, ISAROB. Spinal reflexes greatly contribute to the control of fast physical interactions (e.g., catching a moving ball) without the influence of higher level control systems involved in human motor control. Therefore, to realize the interactions in robots, it is a useful approach to mimic the nervous system controlling spinal reflexes. To this end, as the starting point for creating spinal reflexes, sensors that measure and encode body movements similar to human proprioceptors are needed to generate signals for the spinal reflexes. In this study, we developed artificial muscle proprioceptors to reproduce spinal reflexes in robots. In particular, we focused on pneumatic artificial muscles and designed an artificial muscle spindle and an artificial Golgi tendon organ, which were integrated with a pneumatic artificial muscle. A compact local measuring system consisting of a microcomputer and amplifiers was developed to easily install and organize the sensors.

DOI： 10.1007/s10015-016-0290-9

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2016 IEEE. Stochastic resonance (SR) is a phenomenon occurring in some nonlinear systems by which a signal provided as input that is too small in magnitude to normally influence the system's output can actually influence the system's output once a non-zero level of noise is provided. SR has been extensively studied both theoretically and experimentally, and noise has been exploited for improving the performance in both biological and artificial systems. In addition to its scientific importance, the use of noise has attracted interest because of its potential to overcome the present limitations in engineering applications. In this study, we investigate the use of a universal approximator exploiting SR as a new realization of well-established feed-forward neural networks. The proposed universal approximator consists of groups of threshold elements. Although the approximation universality of a network consisting of threshold elements has been proven in terms of extreme learning machine implementations, once SR is taken into account, the system can be modeled in a form identical to that of a classic generic three-layered neural network, for which the universal approximation capability has been proven. The capability of the proposed approximator for serving as a universal approximator is first proven theoretically in the limit of an infinite number of hidden units. Subsequently, the performance achieved by the backpropagation type and the extreme learning machine type learning algorithms is experimentally evaluated for cases involving limited numbers of hidden units, highlighting the SR effect occurring in the proposed system.

DOI： 10.1109/IJCNN.2016.7727525

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© Springer International Publishing AG 2017. The complex of human foot plays an important role in the locomotion. Properly replicating the human foot characteristics on the humanoid robot foot design is supposed to improve the robot locomotion performance. In this research, we proposed three kinds of foot design, stiff foot, the windlass mechanism foot (with stiff plantar fascia) and the windlass mechanism foot (with elastic plantar fascia). Using a musculoskeletal biped robot and via a large set of dropping jump experiments, we confirmed that (1) the robot could achieve toe-off motion in the lifting off phase of jumping and (2) the windlass mechanism could increase the jumping height. This investigation on robot foot is expected to both improve the humanoid robot jumping performance and help us understanding how human achieve high performance locomotion.

DOI： 10.1007/978-3-319-48036-7_25

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2015 IEEE. Humans can walk stably and adaptively in the presence of various environmental changes. Their bodies have very complex musculoskeletal structures that contribute to their walking stability and adaptability. In this paper, we focus on the gluteus medius, one of muscles contributing to the support of the pelvis. The gluteus medius supports the pelvis when the leg is in a standing position, but it should not inhibit its smooth swing motion. This mechanism is assumed to be realized by the musculoskeletal structure. This paper is devoted to explaining the mechanism by reproducing it using artificial pneumatic muscles. We developed a musculoskeletal robot with a gluteus medius, and showed that the mechanism is well-designed for realizing two seemingly contradictory functions: being stiff to support the pelvis while standing and being smooth to allow swinging. This finding can be utilized for adaptive walking of musculoskeletal humanoid robots.

DOI： 10.1109/IROS.2015.7353925

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2015 IEEE. The aim of this research is to develop a musculoskeletal robot arm, which has a similar mechanical structure to that of a human, to simply make the robot move similarly to a human based on his/her electromyographic signals. In recent years, many musculoskeletal robots have been developed to show advantages of their bio-inspired designs. In this research, we propose a new perspective of their advantages that the control using biological signals can be simplified thanks to the similarity of mechanical structure. To this end, the shoulder complex, which consists of several bones and joints, is focused because it is the most difficult part to develop in humanlike musculoskeletal robot arms. In particular, we develop a linkage mechanism, which can realize similar function to the shoulder complex, to make a surface electromyography(sEMG) based posture control applicable for this complex system. The advantage, that a simple mapping is still available to control the posture to be the same to that of a human, has been successfully shown in an experiment.

DOI： 10.1109/IROS.2015.7353573

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2015 IOP Publishing Ltd. The shoulder complex in the human body consists of the scapula, clavicle, humerus, and thorax and bears the load imposed by arm movements while at the same time realizing a wide range of motions. To mimic and exploit its role, several musculoskeletal robot arms with shoulder complex mechanisms have been developed. However, although many research groups have tried to design the structures using links and joints that faithfully correspond to the bones and joints in the human shoulder complex, its function has not been successfully reproduced because biologically plausible designs seriously compromise engineering plausibility. In this paper, we propose a linkage mechanism that can reproduce complex three-dimensional scapulo movements and considers the trade-off between biological and engineering plausibilities. Subsequently, the design was validated by driving the mechanism using pneumatic artificial muscles (PAMs) placed similarly to muscles in humans. Further, we present experiments in which the robot was controlled by surface electromyographic signals from a human. We show that the proposed design, due to its kinematic similarity with human musculoskeletal systems, eases the conversion between the surface electromyogram signals and the PAMs control inputs.

DOI： 10.1088/1748-3190/10/6/066009

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2015 Ito et al. Background: Quantifying detailed 3-dimensional (3D) kinematics of the foot in contact with the ground during locomotion is crucial for understanding the biomechanical functions of the complex musculoskeletal structure of the foot. Biplanar X-ray fluoroscopic systems and model-based registration techniques have recently been employed to capture and visualise 3D foot bone movements in vivo, but such techniques have generally been performed manually. In the present study, we developed an automatic model-registration method with biplanar fluoroscopy for accurate measurement of 3D movements of the skeletal foot. Methods: Three-dimensional surface models of foot bones were generated prior to motion measurement based on computed tomography. The bone models generated were then registered to biplanar fluoroscopic images in a frame-by-frame manner using an optimisation technique, to maximise similarity measures between occluding contours of the bone surface models with edge-enhanced fluoroscopic images, while avoiding mutual penetration of bones. A template-matching method was also introduced to estimate the amount of bone translation and rotation prior to automatic registration. Results: We analysed 3D skeletal movements of a cadaver foot mobilized by a robotic gait simulator. The 3D kinematics of the calcaneus, talus, navicular and cuboid in the stance phase of the gait were successfully reconstructed and quantified using the proposed model-registration method. The accuracy of bone registration was evaluated as 0.27 ± 0.19 mm and 0.24 ± 0.19° (mean ± standard deviation) in translation and rotation, respectively, under static conditions, and 0.36 ± 0.19 mm and 0.42 ± 0.30° in translation and rotation, respectively, under dynamic conditions. Conclusions: The measurement was confirmed to be sufficiently accurate for actual analysis of foot kinematics. The proposed method may serve as an effective tool for understanding the biomechanical function of the human foot during locomotion.

DOI： 10.1186/s13047-015-0079-4

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2012 IEEE. This paper proposes a learning from demonstration system based on a motion feature, called phase transfer sequence. The system aims to synthesize the knowledge on humanoid whole body motions learned during teacher-supported interactions, and apply this knowledge during different physical interactions between a robot and its surroundings. The phase transfer sequence represents the temporal order of the changing points in multiple time sequences. It encodes the dynamical aspects of the sequences so as to absorb the gaps in timing and amplitude derived from interaction changes. The phase transfer sequence was evaluated in reinforcement learning of sitting-up and walking motions conducted by a real humanoid robot and compatible simulator. In both tasks, the robotic motions were less dependent on physical interactions when learned by the proposed feature than by conventional similarity measurements. Phase transfer sequence also enhanced the convergence speed of motion learning. Our proposed feature is original primarily because it absorbs the gaps caused by changes of the originally acquired physical interactions, thereby enhancing the learning speed in subsequent interactions.

DOI： 10.1109/TNNLS.2014.2333092

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© 2015, Fuji Technology Press. All rights reserved. Stochastic resonance (SR) is a phenomenon by which the addition of random noise improves the detection of weak signals. Thus far, this phenomenon has been extensively studied with the aim of improving sensor sensitivity in various fields of engineering research. However, the possibility of actual application of SR has not been explored because the target signal has to be known in order to confirm the occurrence of SR. In this paper, we propose an optimization method for making SR usable in engineering applications. The underlying mechanism of the proposed method is investigated using information theory and numerical simulation. We developed a tactile sensing system based on the simulation results. The proposed method is applied to this system in order to optimize its parameters for exploiting SR. Results of the experiment show that the developed tactile sensing system successfully achieved higher sensitivity than a conventional system.

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© Springer International Publishing Switzerland 2016. To realize both grasp stability and manipulation dexterity is a central problem in the development of robot hands. In recent years, many underactuated robot hands have been developed that flexibly conform to an object’s surface with simple control. In contrast, it is difficult to realize dexterous manipulation by such underactuated hands in which all degrees of freedom (DoFs) should be controlled. In this research, to realize the dexterous manipulation by simple mechanism and control, we develop a robot gripper comprising of two tendon-driven robotic fingers with nonelastic branching tendons. The branching tendon is a tendon that branches out and connects an actuator to different links. The two joints of this robotic finger are coupled by the nonelastic branching tendon when no external force is exerted. If sufficient external force is applied to the fingertip, one of the tendons slackens and the coupling between the two joints is lost. This means that the two-DoF robotic finger is easily controlled as a single DoF mechanism when reaching toward an object, but when the fingertip is placed on the object, the coupling provided by the branching tendon is released and the finger shifts. Based on this idea, we develop and control a two-DoF robotic finger equipoed with two tendons including a nonelastic branching tendon. We also analyze the conditions, where the branching tendon slacken, and confirmed in an experiment. As the result, the availability of controlling the slack of branched tendon was successfully confirmed.

DOI： 10.1007/978-3-319-08338-4_84

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2014 IEEE. Vertical ground reaction force(vGRF) has been widely known as a qualitative features of human walking. While a human walks, the vGRF exhibits a double peak profile in which two maximal values appear from the heel contact to the toe off. So far, various studies have been mainly conducted in the field of biomechanics to elucidate the mechanism by which the double peak profile of the vGRF can be generated. In these researches, inverted pendulum models that allow the change in the length of the support leg have been considered as one of the minimal models. It is, however, known that the center of mass(COM) trajectory of human waling coincides well with the COM trajectory of the inverted pendulum with constant support leg length because changes in the length of legs during walking is small compared to the length. In this research, we propose a new minimal model for human walking based on the inverted pendulum model with fixed support leg length which can interpret the double peak profile of vGRF by considering double support phase. As a result of the verification by the numerical simulation, the proposed model was successfully confirmed that the double peak profile of vGRF can be reproduced in accordance with the COM trajectory of the inverted pendulum model with fixed support leg length.

DOI： 10.1109/ROBIO.2014.7090544

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2014 IEEE. Direct teaching is suitable for generating motions of robot arms which have complex kinematics. So far, we have proposed a direct teaching method specialized for musculoskeletal robot arms actuated by pneumatic artificial muscles (PAMs) based on their pressure and tension information. In the method, it is important to prevent slacks and excessive tensions of PAMs to efficiently obtain the pressure and the tension information during the teaching phase. In this research, we propose a method for generating active behavior of musculoskeletal robots driven by PAMs to effectively receive human's direct teaching. The method, which is naturally derived from the simple analytical model of PAMs, requires only pressure and tension information of PAMs in musculoskeletal robot arms and does not need to cope with complex inverse kinematics problem. The validity of the method has been confirmed in the experiment using a minimalistic 2DOFs anthropomorphic musculoskeletal robot arm actuated by three pairs of agonist/antagonist PAMs.

DOI： 10.1109/IROS.2014.6943216

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2014 IEEE. Recently, the tendon-driven mechanism with variable joint stiffness has received attention for use in the development of a humanoid robot operated in an uncertain environment with physical contact. In this paper, we propose a mechanism to control the position and joint stiffness of a tendon-driven manipulator independently, using dedicated actuators. This mechanism consists of two parts: a component that transforms the movements of the tendons to activate the actuators, and a component that applies tensile forces to adjust the joint stiffness. We named this mechanism 'tendon routing resolving inverse kinematics' (TRIK). The methodology for designing this mechanism for various tendon-driven manipulators is presented with several examples. We designed TRIK for a manipulator with one degree of freedom and nonconstant-moment arms. Finally, experiments of variable joint stiffness with nonlinearly elastic components were conducted to validate the proposed mechanism.

DOI： 10.1109/IROS.2014.6943108

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

This paper proposes a trajectory control strategy for a tendon-driven robotic finger based on the musculoskeletal system of the human finger. First, we analyzed the relationship between the stereotypical trajectory of the human finger and joint torques generated by the muscles, and hypothesized that the motion of the human finger can be divided into two categories: one following a predetermined trajectory and the other changing the trajectory, which is mainly caused by the action of intrinsic muscles. We applied this control method to an anthropomorphic tendon-driven robotic finger and observed the change in motion caused by adjustments in the actuator's pattern, which corresponds to human intrinsic muscles. © 2014 Springer International Publishing.

DOI： 10.1007/978-3-319-09435-9_25

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Stochastic resonance (SR) is a counterintuitive phenomenon, observed in a wide variety of nonlinear systems, for which the addition of noise of opportune magnitude can improve signal detection. Tuning the noise for maximizing the SR effect is important both for artificial and biological systems. In the case of artificial systems, full exploitation of the SR effect opens the possibility of measuring otherwise unmeasurable signals. In biology, identification of possible SR maximization mechanisms is of great interest for explaining the low-energy high-sensitivity perception capabilities often observed in animals. SR maximization approaches presented in literature use knowledge on the input signal (or stimulus, in the case of living beings), and maximize the mutual information between the input and the output signal. The input signal, however, is unknown in many practical settings. To cope with this problem, this paper introduces an approximation of the input-output mutual information based on the spurious correlation among a set of redundant units. A proof of the approximation, as well as numerical examples of its application are given. © 2014 Elsevier B.V.

DOI： 10.1016/j.cnsns.2014.03.021

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Our paper proposes a tendon-driven robotic finger based on an anatomical model of a human finger and a suitable method for its analysis. Our study aims to realize an anthropomorphic robotic hand that has the same characteristics and dexterity as that of a human hand, and it also aims to identify the advantages of the human musculoskeletal structure for application to the design and control of robot manipulators. When designing an anthropomorphic robotic hand, several devices are required to apply the human finger structure to a tendon-driven robotic finger. Reasons for this include that one of the human finger muscles, namely, the lumbrical muscle, is situated between tendons, which is an unfavorable configuration for the tendon-driven mechanism. Second, unlike a standard pulley used in a tendon-driven mechanism, some moment arms of the human finger change nonlinearly according to the joint angle. In our robotic finger design, we address these difficulties by rearranging its tendons and develop a mechanism to change the moment arm. We also propose a method to analyze and control this robotic fingers coordinating joints using non-stretch branching tendons based on the human extensor mechanism with a virtual tendon Jacobian matrix and the advantage is that this constraint virtually reduces the degrees-of-freedom (DOF) of the mechanism. Further, we build a prototype to confirm its motion using this method. In addition, we show that the state with the reduced DOF can be lost by external forces acting on the mechanism, and this condition can be changed manually by adjusting the tendon forces. This makes it possible to control the virtual DOFs to satisfy the requirements of the task. Finally, we discuss the benefits from anthropomorphic structures including the tendon arrangement, which mimic the human lumbrical muscle, and the above mentioned mechanism with non-linear moment arms from the perspective that there are two states of DOFs. These insights may provide new perspectives in the design of robotic hands. © The Author(s) 2014.

DOI： 10.1177/0278364913518357

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Sarcomere is a functional unit constituting a skeletal muscle, which can only contract and relax in response to changes in Ca+ concentration. In order from the simple to the most complex, it builds structures corresponding to myofibrils, muscle fibers, muscle fiber bundles and the skeletal muscle. This distinctive hierarchical structure of skeletal muscles has been intensively studied in interdisciplinary research fields. In engineering, how the system efficiently controls a large number of sarcomeres to express continuous output force, is a point that has been focused. In this research, we propose a new decentralized control which is very simple but can manage many binary functional units by exploiting environmental noise. The validity of method is confirmed in both numerical simulation and a developed biologically inspired actuator. © 2013 IEEE.

DOI： 10.1109/IROS.2013.6696374

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

In recent years, musculoskeletal robots are being intensively studied to exploit the advantages of biological musculoskeletal systems for robot developments. In these robots, it is very important to assure engineering, biomechanical, and anatomical plausibility at the same time. However, these requirements are often in contradiction. Especially, in the human's shoulder complex, mimicking the glenohumeral joint and the scapulothoracic joint has been difficult because of the need to assure a wide range of movement and the joint's stability at the same time. In this paper, we propose mechanical structures to realize the functions of the glenohumeral joints and scapulothoracic joint. These structures were used to develop a musculoskeletal robot arm driven by pneumatic artificial muscles. In addition, in order to verify the feasibility of the robot arm, we present a dynamic motion in which the robot arm throws a ball by a simple control strategy. © 2012 IEEE.

DOI： 10.1109/IROS.2012.6385950

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Stochastic resonance (SR) is a phenomenon by which the immeasurable input signals of a non-linear system can be observed in the output signals by adding a non-zero level of noise. So far, this phenomenon has been intensively studied, but no methodology for its use in engineering applications has been established yet. To exploit SR in engineering, and, in particular, to determine the appropriate noise variance that optimizes the SR performance, remains an open problem. In this study, we propose a method, which exploits the non- linear correlation between outputs from a set of redundant sensors subject to different noise sources, to tune the noise variance. Because the proposed method does not require the input signal information, it allows the exploitation of SR in realistic engineering problems. The proposed method is validated by information theory and numerical simulations. Based on the results, we developed a tactile sensing system that utilizes the method. Experimental results demonstrate that the tactile sensing system can sense immeasurable signals which are smaller than the quantization error of the sensing system. © 2012 IEEE.

DOI： 10.1109/IROS.2012.6386003

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

The flexor digitorum profundus, extensor digitorum communis and lumbrical muscle of the human hand play a significant role in the movement of the finger. The structure consisting of these muscles and tendons is important to consider an anthropomorphic tendon-driven finger. However, there are some problems to apply the structure found in humans to robotic fingers using mechanical elements. One of them is that the origin of the lumbrical muscle is not on any bones but on the tendon of the flexor digitorum profundus. Another is the non-constant length of the moment arm of the lateral band at the proximal interphalangeal (PIP) joint. We propose a design based on the kinematic model proposed by Leijnse et al. [1] considering the equalization of the joint torques. The proposed model can be easily realized by a structure consisting of actuators fixed to a base and a tendon-pulley system that maintains the function of those three muscle and their tendons. © 2012 IEEE.

DOI： 10.1109/ROBIO.2012.6490995

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© ISAROB 2012. Elementary living beings, like bacteria, are able to reach food sources using only limited and very noisy sensory information. In this paper, we describe a very simple algorithm inspired from bacteria chemotaxis. We present a Markov chain model for studying the effect of noise on the behavior of an agent that moves according to this algorithm, and we show that, counterintuitively, the application of noise can increase the expected average performance over a fixed available time. After this theoretical analysis, experiments on real-world application of this algorithm are introduced. In particular, we show that the algorithm is able to control a complex robot arm, actuated by 17 McKibben pneumatic artificial muscles, without the need of any model of the robot or of its environment.

DOI： 10.1007/s10015-012-0034-4

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記述言語：英語   掲載種別：研究論文（学術雑誌）

© ISAROB 2012. Morphological computation is the concept for which a well-designed hardware can bear part of the computational cost required for robot’s control and perception. So far, many musculoskeletal robots have been developed by taking inspiration from human’s one and shown superior motion performances. The use of pneumatic artificial muscles (PAMs) has been the key to realize these high performance. Additionally, PAMs have the possibility of being used as sensors for environmental information because they are flexible and backdrivable. In this research, we focus on clarifying how PAMs can contribute to morphological computation of robots driven by these actuators. In particular, we propose an analysis method based on transfer entropy and apply this method to the experimental data acquired by a musculoskeletal robot that opens a door.

DOI： 10.1007/s10015-012-0017-5

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記述言語：英語   掲載種別：研究論文（学術雑誌）

This paper describes a self-protective whole body motor controller to enable life-long learning of humanoid robots. In order to reduce the damages on robots caused by physical interaction such as obstacle collision, we introduce self-protective behaviors based on the adaptive coordination of full-body global reactions and local limb reflexes. Global reactions aim at adaptive whole-body movements to prepare for harmful situations. The system incrementally learns a more effective association of the states and global reactions. Local reflexes based on a force-torque sensing function to reduce the impact load on the limbs independently of high-level motor intention. We examined the proposed method with a robot simulator in various conditions. We then applied the systems on a real humanoid robot. © 2012 Elsevier Ltd.

DOI： 10.1016/j.neunet.2012.02.011

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

© 2013 Massachusetts Institute of Technology. A challenging topic in articulated robots is the control of redundantly many degrees of freedom with artificial muscles. Actuation with these devices is difficult to solve because of nonlinearities, delays and unknown parameters such as friction. Machine learning methods can be used to learn control of these systems, but are faced with the additional problem that the size of the search space prohibits full exploration in reasonable time. We propose a novel method that is able to learn control of redundant robot arms with artificial muscles online from scratch using only the position of the end effector, without using any joint positions, accelerations or an analytical model of the system or the environment. To learn in real time, we use the so called online "goal babbling" method to effectively reduce the search space, a recurrent neural network to represent the state of the robot arm, and novel online Gaussian processes for regression. With our approach, we achieve good performance on trajectory tracking tasks for the end effector of two very challenging systems: a simulated 6 DOF redundant arm with artificial muscles, and a 7 DOF robot arm with McKibben pneumatic artificial muscles. We also show that the combination of techniques we propose results in significantly improved performance over using the individual techniques alone.

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記述言語：英語   掲載種別：研究論文（学術雑誌）

In this paper, we describe an anthropomorphic muscular-skeletal robotic upper limb and focus on its soft interaction with the environment. Two experiments are conducted to demonstrate the ability of the system: object recognition by dynamic touch and adaptive door opening. The first experiment shows that the compliant robot is advantageous for categorizing an object by shaking and the second experiment shows that the human-comparable compliant robot can open a door without precise control. The robot is expected to have comparable anisotropic compliance to that of a human, which can be utilized for realization of human-like adaptive behavior. © Koninklijke Brill NV, Leiden and The Robotics Society of Japan.

DOI： 10.1163/156855312X625371

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Close physical interaction between robots and humans is a particularly challenging aspect of robot development. For successful interaction and cooperation, the robot must have the ability to adapt its behavior to the human counterpart. Based on our earlier work, we present and evaluate a computationally efficient machine learning algorithm that is well suited for such close-contact interaction scenarios. We show that this algorithm helps to improve the quality of the interaction between a robot and a human caregiver. To this end, we present two human-in-the-loop learning scenarios that are inspired by human parenting behavior, namely, an assisted standing-up task and an assisted walking task. © 1994-2011 IEEE.

DOI： 10.1109/MRA.2011.2181676

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Animals are able to cope with the noise, uncertainties, and complexity of the real world. Often even elementary living beings, equipped with very limited sensory organs, are able to reach regions favorable to their existence, using simple stochastic policies. In this paper we discuss a minimalistic stochastic behavioral rule, inspired from bacteria chemotaxis, which is able to increase the value of a specified evaluation function in a similar manner. In particular, we prove that, under opportune assumptions, the direction that is taken with maximum probability by an agent that follows this rule corresponds to the optimal direction. The rule does not require a specific agent dynamics, needs no memory for storing observed states, and works in generic n-dimensional spaces. It thus reveals itself interesting for the control of simple sensing robots as well. © 2012 American Physical Society.

DOI： 10.1103/PhysRevE.85.021905

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

This paper presents a direct teaching method for musculoskeletal robots driven by pneumatic artificial muscles (PAMs). In order to reproduce motions which are directly taught by a human, it is necessary to reproduce the lengths of PAMs because they geometrically determine the posture assumed by the robot. However, it is difficult to measure the lengths of PAMs because mounting length sensors is space-consuming. Additionally, estimating lengths is also difficult because it is required to know the intrinsic parameters of PAMs which are extremely difficult to measure for each muscle. In order to overcome the above problems, the proposed method calculates the desired internal pressures or the desired axial tensions of the PAMs under a specific constraint, which forces PAM's lengths in the reproducing phase to be similar to the lengths during the teaching phase. In this way, it is possible to reproduce the motion by controlling the internal pressures or the axial tensions instead of the lengths. The validity was confirmed through an experiment using a real musculoskeletal robot arm. © 2012 IEEE.

DOI： 10.1109/ICRA.2012.6224999

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

This paper describes a self-protective whole-body control method for humanoid robots. A set of postural reactions are used to create whole-body movements. A set of reactions is merged to cope with a general falling down direction, while allowing the upper limbs to contact safely with obstacles. The collision detection is achieved by force sensing. We verified that our method generates the self-protective motion in real time, and reduced the impact energy in multiple situations by simulator. We also verified that our systems works adequately in real-robot. © 2011 IEEE.

DOI： 10.1109/IJCNN.2011.6033596

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Some bacteria present a movement which can be modeled as a biased random walk. Biased random walk can be used also for artificial creatures as a very simple and robust control policy for tasks like goal reaching. In this paper, we show how a very simple control law based on random walk is able to guide mobile robot equipped with an omnidirectional camera toward a target without any knowledge about the robot's actuators or about the robot's camera parameters. We verified, by several simulation experiments, the robustness of the random biased control law with respect to failures of robot's actuators or sensor damages. These damages are similar to the ones which can occur during a RoboCup match. The tests show that the optimal behavior is obtained using a bias which is roughly proportional to the random walk step, with a coefficient dependent on the physical structure of the robot, on its actuators and on and its sensors after the damage. Finally, we validated the proposed approach with experiments in the real world with a wheeled robot performing a goal reaching task in a Middle-Size RoboCup field without any prior knowledge on the actuators and without any calibration of the very noisy omnidirectional camera mounted on the robot. © 2011 Springer-Verlag.

DOI： 10.1007/978-3-642-20217-9_19

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Stochastic resonance (SR) is a phenomenon occurring in nonlinear systems by which the ability to process information, for instance the detection of weak signals is statistically enhanced by a non-zero level of noise. SR effects have been observed in a great variety of systems, comprising electronic circuits, optical devices, chemical reactions and neurons. In this paper we report the SR phenomena occurring in the execution of an extremely simple behavioral rule inspired from bacteria chemotaxis. The phenomena are quantitatively analyzed by using Markov chain models and Monte Carlo simulations. © 2011 Elsevier Ltd.

DOI： 10.1016/j.jtbi.2011.01.002

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記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

A biologically inspired control algorithm for robot control was introduced in a previous work. The algorithm is robust to noisy sensor information and hardware failures. In this paper a new version of the algorithm is presented. The new version is able to cope with highly non-linear systems and presents an improved robustness to low-pass filter effects and dead-times. Automatic tuning of the parameters is also introduced, providing a completely parameterless algorithm. © 2010 Springer-Verlag Berlin Heidelberg.

DOI： 10.1007/978-3-642-17319-6_34

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