Motion planning control for multiple car-like robots using the Bump-Surface concept

This paper presents a new approach for intelligent control of multiple car-like robots moving in a 2D environment cluttered with both static and moving obstacles. The objective is to determine simultaneously the global near-optimum collision-free path for each robot. The proposed approach consists of three main phases: The space-time is formulated to represent the moving obstacles as time-depended obstacles. Then, the Bump-Surface concept is used to represent the 3D Space-Time by a 3D B-Spline surface embedded in 4D Euclidean space. The robots motions are represented by 3D B-Spline curves on the 3D Bump-Surface and the global optimal paths are being searched on the generated Bump-Surface using a genetic algorithm (GA). The performance of the proposed approach is investigated through a large number of experiments in various simulated 2D dynamic environments.