Abstract
The design and implementation of particle swarm optimization (PSO) gait learning method for adult-sized humanoid robots is proposed in this paper. In order to reduce the motor damage and let train motions more convenient, a robotics simulator system for humanoid robots is designed. This robotics simulator system is established by an open source software-Open Dynamics Engine (ODE). The model of David developed by aiRobots laboratory is a combination of rigid bodies and joints. The humanoid robot is trained on the robotics simulator system with PSO method, which chooses the trajectory of robot's center of mass as the fitness value to learn faster and stable gait automatically. The results of the experiment show that the motions which play on the robotics simulator system are very similar to the real motions, so it can be utilized as the motion training platform. The result of the PSO gait learning method has great performance on the robotics simulator system. The humanoid robot learns gait pattern from marking time to moving center of mass and swing its legs. Finally, this gait let the real humanoid robot walk forward at 14.5 cm/s.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 |
| Pages | 2683-2688 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2013 Dec 1 |
| Event | 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 - Manchester, United Kingdom Duration: 2013 Oct 13 → 2013 Oct 16 |
Publication series
| Name | Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 |
|---|
Other
| Other | 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 |
|---|---|
| Country | United Kingdom |
| City | Manchester |
| Period | 13-10-13 → 13-10-16 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Human-Computer Interaction
Cite this
}
Development of humanoid robot simulator for gait learning by using particle swarm optimization. / Kuo, Ping Huan; Ho, Ya Fang; Lee, Kai Fan; Tai, Li Heng; Li, Tzuu-Hseng S.
Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013. 2013. p. 2683-2688 6722211 (Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Development of humanoid robot simulator for gait learning by using particle swarm optimization
AU - Kuo, Ping Huan
AU - Ho, Ya Fang
AU - Lee, Kai Fan
AU - Tai, Li Heng
AU - Li, Tzuu-Hseng S.
PY - 2013/12/1
Y1 - 2013/12/1
N2 - The design and implementation of particle swarm optimization (PSO) gait learning method for adult-sized humanoid robots is proposed in this paper. In order to reduce the motor damage and let train motions more convenient, a robotics simulator system for humanoid robots is designed. This robotics simulator system is established by an open source software-Open Dynamics Engine (ODE). The model of David developed by aiRobots laboratory is a combination of rigid bodies and joints. The humanoid robot is trained on the robotics simulator system with PSO method, which chooses the trajectory of robot's center of mass as the fitness value to learn faster and stable gait automatically. The results of the experiment show that the motions which play on the robotics simulator system are very similar to the real motions, so it can be utilized as the motion training platform. The result of the PSO gait learning method has great performance on the robotics simulator system. The humanoid robot learns gait pattern from marking time to moving center of mass and swing its legs. Finally, this gait let the real humanoid robot walk forward at 14.5 cm/s.
AB - The design and implementation of particle swarm optimization (PSO) gait learning method for adult-sized humanoid robots is proposed in this paper. In order to reduce the motor damage and let train motions more convenient, a robotics simulator system for humanoid robots is designed. This robotics simulator system is established by an open source software-Open Dynamics Engine (ODE). The model of David developed by aiRobots laboratory is a combination of rigid bodies and joints. The humanoid robot is trained on the robotics simulator system with PSO method, which chooses the trajectory of robot's center of mass as the fitness value to learn faster and stable gait automatically. The results of the experiment show that the motions which play on the robotics simulator system are very similar to the real motions, so it can be utilized as the motion training platform. The result of the PSO gait learning method has great performance on the robotics simulator system. The humanoid robot learns gait pattern from marking time to moving center of mass and swing its legs. Finally, this gait let the real humanoid robot walk forward at 14.5 cm/s.
UR - http://www.scopus.com/inward/record.url?scp=84893606684&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893606684&partnerID=8YFLogxK
U2 - 10.1109/SMC.2013.457
DO - 10.1109/SMC.2013.457
M3 - Conference contribution
SN - 9780769551548
T3 - Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
SP - 2683
EP - 2688
BT - Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
ER -