The Particle Swarm Optimization: A Flexible Approach to Generate Robots Behaviors

Abstract. We describe in this contribution a unified controller we implemented in order to simplify creating behaviors and interaction metaphors robots may have with human users. This controller is based on a multi-objective optimiza-tion technique allowing simultaneous achievement of different constraints and goals. The core of the developed algorithm is based on the particle swarm opti-mization technique (PSO). Through some examples, namely, a wheeled robot following persons in populated and cluttered environments and a humanoid reaching for objects, we show how the PSO is effective in solving the given problems in flexible and generic ways. We detail in this paper the algorithm and give some results obtained from simulations and field trials