Abstract
This paper proposes a new feed-forward positioning method for a musculoskeletal-like robotic system considering a muscle-like nonlinear viscosity, and a new determination method of the internal force using the reinforcement learning scheme. In our previous works, a feed-forward positioning method for the musculoskeletal-like robotic systems has been proposed. In the method, the position regulation of the system can be accomplished by inputting a desired internal force balancing at a desired position. It has been quite effective for the muscle-like driven mechanism because no sensor is necessary to regulate the position. However, this method often induces an overshoot phenomenon when performing a set-point control. In addition, there is another intrinsic problem that musculoskeletal-like redundant-driven mechanisms own the ill-posed problems that the internal force is unable to determine uniquely. In this paper, for the farmer problem, a muscle-like nonlinear viscosity is newly added to the controller to reduce such an overshoot phenomenon and then to expand the stable region of the manipulator. For the latter problem, a determination method of the internal force using a reinforcement learning scheme is newly proposed. In what follows, firstly a new feed-forward controller which considers the muscle-like viscosity is introduced, and shows its effectiveness through numerical simulations. Next, the determination method of the internal force using a reinforcement learning scheme is proposed and its effectiveness is also shown through numerical simulations.
| Original language | English |
|---|---|
| Title of host publication | 2013 IEEE Workshop on Advanced Robotics and Its Social Impacts, ARSO 2013 - Conference Digest |
| Pages | 7-12 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2013 |
| Event | 2013 IEEE Workshop on Advanced Robotics and Its Social Impacts, ARSO 2013 - Tokyo, Japan Duration: Nov 7 2013 → Nov 9 2013 |
Other
| Other | 2013 IEEE Workshop on Advanced Robotics and Its Social Impacts, ARSO 2013 |
|---|---|
| Country | Japan |
| City | Tokyo |
| Period | 11/7/13 → 11/9/13 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
Cite this
Feed-forward positioning of musculoskeletal-like robotic systems with muscular viscosity : Determination of an adequate internal force. / Matsutani, Yuki; Ochi, Hiroaki; Kino, Hitoshi; Tahara, Kenji; Yamamoto, Motoji.
2013 IEEE Workshop on Advanced Robotics and Its Social Impacts, ARSO 2013 - Conference Digest. 2013. p. 7-12 6705498.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Feed-forward positioning of musculoskeletal-like robotic systems with muscular viscosity
T2 - Determination of an adequate internal force
AU - Matsutani, Yuki
AU - Ochi, Hiroaki
AU - Kino, Hitoshi
AU - Tahara, Kenji
AU - Yamamoto, Motoji
PY - 2013
Y1 - 2013
N2 - This paper proposes a new feed-forward positioning method for a musculoskeletal-like robotic system considering a muscle-like nonlinear viscosity, and a new determination method of the internal force using the reinforcement learning scheme. In our previous works, a feed-forward positioning method for the musculoskeletal-like robotic systems has been proposed. In the method, the position regulation of the system can be accomplished by inputting a desired internal force balancing at a desired position. It has been quite effective for the muscle-like driven mechanism because no sensor is necessary to regulate the position. However, this method often induces an overshoot phenomenon when performing a set-point control. In addition, there is another intrinsic problem that musculoskeletal-like redundant-driven mechanisms own the ill-posed problems that the internal force is unable to determine uniquely. In this paper, for the farmer problem, a muscle-like nonlinear viscosity is newly added to the controller to reduce such an overshoot phenomenon and then to expand the stable region of the manipulator. For the latter problem, a determination method of the internal force using a reinforcement learning scheme is newly proposed. In what follows, firstly a new feed-forward controller which considers the muscle-like viscosity is introduced, and shows its effectiveness through numerical simulations. Next, the determination method of the internal force using a reinforcement learning scheme is proposed and its effectiveness is also shown through numerical simulations.
AB - This paper proposes a new feed-forward positioning method for a musculoskeletal-like robotic system considering a muscle-like nonlinear viscosity, and a new determination method of the internal force using the reinforcement learning scheme. In our previous works, a feed-forward positioning method for the musculoskeletal-like robotic systems has been proposed. In the method, the position regulation of the system can be accomplished by inputting a desired internal force balancing at a desired position. It has been quite effective for the muscle-like driven mechanism because no sensor is necessary to regulate the position. However, this method often induces an overshoot phenomenon when performing a set-point control. In addition, there is another intrinsic problem that musculoskeletal-like redundant-driven mechanisms own the ill-posed problems that the internal force is unable to determine uniquely. In this paper, for the farmer problem, a muscle-like nonlinear viscosity is newly added to the controller to reduce such an overshoot phenomenon and then to expand the stable region of the manipulator. For the latter problem, a determination method of the internal force using a reinforcement learning scheme is newly proposed. In what follows, firstly a new feed-forward controller which considers the muscle-like viscosity is introduced, and shows its effectiveness through numerical simulations. Next, the determination method of the internal force using a reinforcement learning scheme is proposed and its effectiveness is also shown through numerical simulations.
UR - http://www.scopus.com/inward/record.url?scp=84894177106&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84894177106&partnerID=8YFLogxK
U2 - 10.1109/ARSO.2013.6705498
DO - 10.1109/ARSO.2013.6705498
M3 - Conference contribution
SN - 9781479923694
SP - 7
EP - 12
BT - 2013 IEEE Workshop on Advanced Robotics and Its Social Impacts, ARSO 2013 - Conference Digest
ER -