Stealth Terrain Navigation for Multi-Vehicle Path Planning

In this paper, we propose a method for solving visibility-based terrain path planning problems for groups of vehicles using data parallel machines. The discussion focuses on path planning for two groups of vehicles so that they move in a bounding overwatch manner. Furthermore, the planned paths for the vehicles themselves are subject to intervisibility constraints, configuration constraints, and different terrain traversabilities due to variations in terrain type and slope. A spatial-temporal sampling approach is adopted to discretize the solution space and facilitate fast computation on a data parallel machine. One of the key computations in the planning is the region-to-region visibility analysis, which is computationally expensive but essential to the choice of subgoals to carry out reconnaissance activities. A parallel algorithm for this analysis is developed. By reducing the communication complexity, our algorithm achieves much faster running time than traditional methods. The algorithms are implemented on a Connection Machine CM-2, and the experimental results show that the planning system effectively generates good paths.