Real-time path planning for navigation in unknown environment

摘要

Real-time path planning is a challenging task that has many applications in the fields of AI, moving robots, virtual reality, agent behavior simulation, and action games. The various approaches for path planning have different criteria that have to be met, resulting in a number of algorithms for solutions to specific problems. In this paper, we introduce our approach and recent development regarding path planning in game environments. We propose a real-time motion-optimization algorithm called Adaptive Dynamic Points of Visibility (ADPV) for navigation of vehicles or moving agents in dynamical unconfigured environments, which computes a collision-free, time-optimal motion track for the moving objects. Our approach is able to deal with the obstacle-space that is unknown or partially unknown to the moving agent. It therefore solves the drawbacks of traditional obstacle-space configuration methods.