Multi-objective parameter CPG optimization for gait generation of a quadruped robot considering behavioral diversity

This paper presents a gait multi-objective optimization system that combines bio-inspired Central Patterns Generators (CPGs) and a multi-objective evolutionary algorithm. CPGs are modeled as autonomous differential equations, that generate the necessary limb movement to perform the required walking gait. In order to optimize the walking gait, four conflicting objectives are considered, simultaneously: minimize the body vibration, maximize the velocity, maximize the wide stability margin and maximize the behavioral diversity. The results of NSGA-II for this multi-objective problem are discussed. The effect of the inclusion of a behavioral diversity objective in the system is also studied in terms of the walking gait achieved. The experimental results show the effectiveness of this multi-objective approach. The several walking gait solutions obtained correspond to different trade-off between the objectives.
This work is funded by FEDER Funding supported by the Operational Program Competitive Factors - COMPETE and National Funding supported by the FCT - Portuguese Science Foundation through project PTDC/EEACRO/ 100655/2008. Thanks to Dr. St ? ephane Doncieux from the Institut des Systmes Intelligents et de Robotique (ISIR) of the Pierre and Marie Curie University (UPMC)