Webots-based simulator for biped navigation in human-living environments

Navigation is one of the key issues of biped robot, especially in complicated and uncertain human-living environment. There have been challenges for ensuring the stability, efficiency and security of the biped navigation system. In this paper, a framework utilizing sampling-based footstep planner is proposed for the simulation of the biped navigation. Sensor fusion method is adopted to process and generate the correlated environment information for footstep planning. Two specific experiments have been conducted to validate the functionality and performance of the proposed framework.

[1]  Ken Chen,et al.  A deterministic sampling-based approach to global footstep planning for humanoid robots , 2009, 2009 9th IEEE-RAS International Conference on Humanoid Robots.

[2]  G. Swaminathan.  Robot Motion Planning , 2006 .

[3]  Masayuki Inaba,et al.  Footstep planning among obstacles for biped robots , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[4]  J. Chestnutt,et al.  Planning Biped Navigation Strategies in Complex Environments , 2003 .

[5]  Satoshi Kagami,et al.  An adaptive action model for legged navigation planning , 2007, 2007 7th IEEE-RAS International Conference on Humanoid Robots.

[6]  Ken Chen,et al.  Parameter self-adaptation in biped navigation employing nonuniform randomized footstep planner , 2010, Robotica.

[7]  Auke Jan Ijspeert,et al.  Central pattern generators for locomotion control in animals and robots: A review , 2008, Neural Networks.

[8]  Olivier Michel,et al.  Cyberbotics Ltd. Webots™: Professional Mobile Robot Simulation , 2004, ArXiv.

[9]  Masayuki Inaba,et al.  Motion Planning for Humanoid Robots , 2003, ISRR.

[10]  Ken Chen,et al.  Global Navigation for Humanoid Robots Using Sampling-Based Footstep Planners , 2011, IEEE/ASME Transactions on Mechatronics.

[11]  R. Pfeifer,et al.  Self-Organization, Embodiment, and Biologically Inspired Robotics , 2007, Science.