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Legged balance on moving table by reinforcement learning
- Source :
- 2020 20th International Conference on Control, Automation and Systems (ICCAS).
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- Balancing is one of the most essential ability for legged robots. From maintaining posture on unstable surfaces to withstanding sudden force disturbances, balancing is widely used in rescue robots. Among these various balancing issues, this study focused on balancing on moving plates. The study is applicable when the robot needs to perform an operation on an earthquake or shaking ship environment. In addition, since ZMP(Zero Moment Point) is used for the control, the performance is exhibited not only when an external force is applied such as wind force, but also an inertial force is exerted. In this study, reinforcement learning was used so that the proposed algorithm can avoid redundancy issues and kinematic singularities which cause problems in traditional method. The simulation results show how this new approach can improve the robot’s balancing ability.
- Subjects :
- Rescue robot
0209 industrial biotechnology
Robot kinematics
Computer science
020208 electrical & electronic engineering
02 engineering and technology
Kinematics
020901 industrial engineering & automation
Control theory
Fictitious force
0202 electrical engineering, electronic engineering, information engineering
Redundancy (engineering)
Reinforcement learning
Robot
Zero moment point
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 20th International Conference on Control, Automation and Systems (ICCAS)
- Accession number :
- edsair.doi...........1b339301f18e1eb08907e94195d31e47