Résumé: This paper is a presentation of a work that consists to model a biped robot walk in simulation. The specific objective is to develop a strategy based on an evolutionary method. The chosen architecture to represent the biped includes ten degrees of freedom on ten articulations between seven links. This evolutionary method is a generation of articulation angles using a particle swarm optimization (PSO). This work invokes also the direct kinematic principle. The PSO guarantees the stability of the biped by using a constraint on the center of mass (CoM) and the polygon of support. Results show that this method is tempting for a high level development.

Résumé: This paper discusses the bio-inspired algorithm of the Particle Swarm Optimisation (PSO) for a wheeled robot’s displacement. PSO was selected because its flexibility and its tempting results. An omnidirectional wheeled robot was simulated on a flat environment with two tasks: ‘Reach a goal’ or ‘collect balls’. This paper checks on the performance of PSO for the displacement studied. In the first case, we discussed the variation of execution time compared to the particles’ and the neighbours’ number. In the second one, we studied the change in the path’s length compared to execution time depending on the particles’ and balls’ number.

Résumé: This paper presents the use of a bio-inspired method in robotics research. We discuss the Particle swarm optimization (PSO) for two ground robots: an omnidirectional rolling robot and a biped walker robot. For the wheeled robot, we studied the navigation in a flat environment with eventual obstacles. Thus, for the biped robot, we applied on the gesture of the straight walk. The PSO algorithm shows that is very tempting for contribution in the evolutionary robotics researches.