Title :
Quasi optimal gait for a biped robot using genetic algorithm
Author :
Cabodevila, Gonzalo ; Abba, Gabriel
Author_Institution :
Groupe de Recherche en Autom. et Vision Robotique, Illkirch, France
Abstract :
The context of our research is the study of legged robots. In order to realize autonomous legged robots, the energy consumption during a step should be minimized. The method proposed is based on the expansion in Fourier´s series of the joint trajectories. Thus, the search of optimal trajectories is converted into a nonlinear programming problem. The convergence cannot be guaranteed if a constraint (the floor) is introduced, since the cost function becomes highly nonlinear and multi modal. The incorporation of this constraint in terms of a simplified model for the floor and the contact force significantly improve the algorithm´s convergence
Keywords :
energy conservation; genetic algorithms; legged locomotion; minimisation; nonlinear programming; position control; Fourier series; algorithm convergence; autonomous legged robots; biped robot; contact force; cost function; energy consumption; genetic algorithm; joint trajectories; nonlinear programming problem; optimal trajectories; quasi optimal gait; simplified model; Convergence; Cost function; Fourier series; Genetic algorithms; Leg; Legged locomotion; Mobile robots; Robot vision systems; Robotics and automation; Torque;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.633290