Multi-objective optimisation for humanoid robot motion planning

Single objective optimisation method is primarily adopted to solve humanoid robot gait optimisation problems. However, this method has certain limitations because it can consider only one objective function, such as energy, stability, or speed. This study presents a method based on the improved Non-Dominated Sorting Genetic Algorithm-II NSGA-II and parametric control technique to optimise the parameters of the humanoid robot when walking up and down a slope. We propose a novel non-dominated sorting method based on a self-adjusting binary search tree, which overcomes the low efficiency of the traditional fast non-dominated sorting. We use the improved NSGA-II with this new non-dominated sorting method to achieve multi-objective optimisation of the gait parameters for a humanoid robot walking on a slope. Experiment results indicated that this method is effective and can better realise gait planning for humanoid robots walking on a slope.

[1]  Sani Irwan Md Salim,et al.  3-D Biped Robot Walking along Slope with Dual Length Linear Inverted Pendulum Method (DLLIPM) , 2013 .

[2]  Yang Dong,et al.  Research on Evolutionary Multi-Objective Optimization Algorithms , 2009 .

[3]  Prahlad Vadakkepat,et al.  Genetic algorithm-based optimal bipedal walking gait synthesis considering tradeoff between stability margin and speed , 2009, Robotica.

[4]  Qian Wang,et al.  An Efficient Non-dominated Sorting Method for Evolutionary Algorithms , 2008, Evolutionary Computation.

[5]  Robert E. Tarjan,et al.  Self-adjusting binary search trees , 1985, JACM.

[6]  Alistair Moffat,et al.  Splaysort: fast, versatile, practical , 1996 .

[7]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[8]  Kalyanmoy Deb,et al.  MULTI-OBJECTIVE FUNCTION OPTIMIZATION USING NON-DOMINATED SORTING GENETIC ALGORITHMS , 1994 .

[9]  Vítor Matos,et al.  Multi-objective parameter CPG optimization for gait generation of a quadruped robot considering behavioral diversity , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Kalyanmoy Deb,et al.  Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms , 1994, Evolutionary Computation.

[11]  Vítor Matos,et al.  Multi-objective parameter CPG optimization for gait generation of a biped robot , 2013, 2013 IEEE International Conference on Robotics and Automation.

[12]  Changjiu Zhou,et al.  Dynamically stable gait planning for a humanoid robot to climb sloping surface , 2004, IEEE Conference on Robotics, Automation and Mechatronics, 2004..

[13]  Carlos Canudas-de-Wit,et al.  Generation of energy optimal complete gait cycles for biped robots , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[14]  Friedrich Pfeiffer,et al.  Optimization based gait pattern generation for a biped robot , 2005, 5th IEEE-RAS International Conference on Humanoid Robots, 2005..

[15]  Cord Niehaus,et al.  Gait Optimization on a Humanoid Robot using Particle Swarm Optimization , 2007 .

[16]  Chee-Meng Chew,et al.  Optimized Joint-Torques Trajectory Planning for Bipedal Walking Robots , 2008, 2008 IEEE Conference on Robotics, Automation and Mechatronics.

[17]  Jong-Wook Kim,et al.  Generation of optimal trajectories for ascending and descending a stair of a humanoid based on uDEAS , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[18]  Leonard Barolli,et al.  Application of Genetic Algorithms for biped robot gait synthesis optimization during walking and going up-stairs , 2001, Adv. Robotics.

[19]  N Kaewlek,et al.  Inclined plane walking compensation for a humanoid robot , 2010, ICCAS 2010.

[20]  Gwi-Tae Park,et al.  Use of Support Vector Machines: Synergism to Intelligent Humanoid Robot Walking Down on a Slope , 2006, KES.

[21]  S. Kajita,et al.  Experimental study of biped dynamic walking , 1996 .

[22]  Nikolaos G. Tsagarakis,et al.  Stabilization for the compliant humanoid robot COMAN exploiting intrinsic and controlled compliance , 2012, 2012 IEEE International Conference on Robotics and Automation.

[23]  Miomir Vukobratovic,et al.  Zero-Moment Point - Thirty Five Years of its Life , 2004, Int. J. Humanoid Robotics.

[24]  Guy Bessonnet,et al.  A Parametric Optimization Approach to Walking Pattern Synthesis , 2005, Int. J. Robotics Res..

[25]  Mikkel T. Jensen,et al.  Reducing the run-time complexity of multiobjective EAs: The NSGA-II and other algorithms , 2003, IEEE Trans. Evol. Comput..