Active balance of humanoids with foot positioning compensation and non-parametric adaptation |
| |
| Affiliation: | 1. School of Electronics and Information Engineering, Tongji University, Shanghai, China;2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore;1. Advanced Image Research Lab (ARIL), Samsung Semiconductor Inc., Pasadena, CA, 91103, United States;2. Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, United States;1. Department of Mechatronic Engineering, University of Isfahan, Isfahan, Iran;2. Department of Computer Engineering, University of Isfahan, Isfahan, Iran;1. École Polytechnique Fédérale de Lausanne, Switzerland;2. University of Bologna, Italy;3. TU Munich, Germany |
| |
| Abstract: | To maintain human-like active balance for a humanoid robot, this paper proposes a novel adaptive non-parametric foot positioning compensation approach that can modify predefined step position and step duration online with sensor feedback. A constrained inverted pendulum model taking into account of supporting area to CoM acceleration is used to generate offline training samples with constrained nonlinear optimization programming. To speed up real-time computation and make online model adjustable, a non-parametric regression model based on extended Gaussian Process model is applied for online foot positioning compensation. In addition, a real-time and sample-efficient local adaptation algorithm is proposed for the non-parametric model to enable online adaptation of foot positioning compensation on a humanoid system. Simulation and experiments on a full-body humanoid robot validate the effectiveness of the proposed method. |
| |
| Keywords: | Humanoid walking Active balance Foot positioning compensation Gaussian process |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
