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Your search keyword '"Nakajima, Kohei"' showing total 27 results
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27 results on '"Nakajima, Kohei"'

13. Behavior switching by using reservoir computing for a soft robotic arm

Author

Li, Tao, Nakajima, Kohei, Cianchetti, Matteo, Laschi, Cecilia, Pfeifer, Rolf, Li, Tao, Nakajima, Kohei, Cianchetti, Matteo, Laschi, Cecilia, and Pfeifer, Rolf

Abstract

Soft robots have significant advantages over traditional robots made of rigid materials. However, controlling this type of robot by conventional approaches is difficult. Reservoir computing has been demonstrated to be an effective approach for achieving rapid learning in benchmark tasks and conventional robots. In this study, we investigated the feasibility and capacity of the reservoir computing approach to embedding and switching between multiple behaviors in a on-line manner in a soft robotic arm. The result shows that this approach can successfully achieve this task.

Published
2012

27. Spine dynamics as a computational resource in spine-driven quadruped locomotion.

Author

Zhao, Qian, Nakajima, Kohei, Sumioka, Hidenobu, Hauser, Helmut, and Pfeifer, Rolf

Abstract

Recent results suggest that compliance and non-linearity in physical bodies of soft robots may not be disadvantageous properties with respect to control, but rather of advantage. In the context of morphological computation one could see such complex structures as potential computational resources. In this study, we implement and exploit this view point in a spine-driven quadruped robot called Kitty by using its flexible spine as a computational resource. The spine is an actuated multi-joint structure consisting of a sequence of soft silicone blocks. Its complex dynamics are captured by a set of force sensors and used to construct a closed-loop to drive the motor commands. We use simple static, linear readout weights to combine the sensor values to generate multiple gait patterns (bounding, trotting, turning behavior). In addition, we demonstrate the robustness of the setup by applying strong external perturbations in form of additional loads. The system is able to fully recover to its nominal gait patterns (which are encoded in the linear readout weights) after the perturbation has vanished. [ABSTRACT FROM PUBLISHER]

Published
2013
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