An Integrated Motion Planner/Controller for Humanoid Robots on Uneven Ground

We consider a situation in which a humanoid robot must reach a goal region (walk-to task) walking in an environment consisting of horizontal patches located at different heights (world of stairs). To solve this problem, the paper proposes an integrated motion planner/controller working in two stages: off-line footstep planning and on-line gait generation. The planning stage is based on a randomized algorithm that efficiently searches for a feasible footstep sequence. The gait generation uses an intrinsically stable MPC-based control scheme which computes CoM trajectories that are suitable for walking on uneven ground. The proposed framework was implemented in the V-REP environment for the HRP4 humanoid robot and successfully tested via simulations.

[1]  Maren Bennewitz,et al.  Anytime search-based footstep planning with suboptimality bounds , 2012, 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012).

[2]  Takeo Kanade,et al.  Footstep Planning for the Honda ASIMO Humanoid , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[3]  Giuseppe Oriolo,et al.  Intrinsically stable MPC for humanoid gait generation , 2016, 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids).

[4]  Takahide Yoshiike,et al.  Dynamic gait transition between bipedal and quadrupedal locomotion , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[5]  Adrien Escande,et al.  Capturability-Based Pattern Generation for Walking With Variable Height , 2018, IEEE Transactions on Robotics.

[6]  Olivier Stasse,et al.  Fast Humanoid Robot Collision-Free Footstep Planning Using Swept Volume Approximations , 2012, IEEE Transactions on Robotics.

[7]  Giuseppe Oriolo,et al.  Humanoid Gait Generation on Uneven Ground using Intrinsically Stable MPC ⁎ , 2018, SyRoCo.

[8]  Ken Chen,et al.  A random sampling-based approach to goal-directed footstep planning for humanoid robots , 2009, 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[9]  Abderrahmane Kheddar,et al.  Dynamic walking over rough terrains by nonlinear predictive control of the floating-base inverted pendulum , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[10]  Yasuo Kuniyoshi,et al.  Online gait planning with Dynamical 3D-Symmetrization method , 2007, 2007 7th IEEE-RAS International Conference on Humanoid Robots.

[11]  Kazuhito Yokoi,et al.  Biped walking pattern generation by using preview control of zero-moment point , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[12]  Shuuji Kajita,et al.  Study of dynamic biped locomotion on rugged terrain-derivation and application of the linear inverted pendulum mode , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[13]  Robin Deits,et al.  Footstep planning on uneven terrain with mixed-integer convex optimization , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

[14]  Dennis W. Hong,et al.  Humanoid locomotion on uneven terrain using the time-varying divergent component of motion , 2014, 2014 IEEE-RAS International Conference on Humanoid Robots.

[15]  Pierre-Brice Wieber,et al.  Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong Perturbations , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.

[16]  Andrei Herdt Model predictive control of a humanoid robot , 2012 .

[17]  Wolfram Burgard,et al.  World Modeling , 2008, Springer Handbook of Robotics.

[18]  Alin Albu-Schäffer,et al.  Three-Dimensional Bipedal Walking Control Based on Divergent Component of Motion , 2015, IEEE Transactions on Robotics.

[19]  Chun-Hung Chen,et al.  Arbitrary biped robot foot gaiting based on variate COM height , 2013, 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).