Generating timed trajectories for an autonomous vehicle: a non-linear dynamical systems approach

Abstract

The timing of movements and of action sequences is important when particular events must be achieved in time-varying environments, avoiding moving obstacles or coordinating multiple robots. However, timing is difficult when it must be compatible with continuous on-line coupling to low-level and often noisy sensory information which is used to initiate and steer action. We extended the Dynamic Approach to Behavior Generation to account for timing constraints. We proposed a solution that uses a dynamical system architecture to autonomously generate timed trajectories and sequences of movements as attractor solutions of dynamic systems. The model consists of a two layer architecture, in which a competitive "neural" dynamics layer controls the qualitative dynamics of a second, "timing" layer. The second layer generates both stable oscillations and stationary states, such that periodic attractors generate timed movement. The first layer controls the switching between the limit cycle and the fixed points, allowing for discrete movements and movement sequences. This model was integrated with another dynamical system without timing constraints. The complete dynamical architecture was demonstrated on a vision-guided mobile robot in real time, whose goal is to reach a target in approximately constant time within a non-structured environment. The obtained results illustrated the stability and flexibility properties of the timing architecture as well as the robustness of the proposed decision-making mechanism.