Optimal Global Path Planning in Time Varying Environments Based on a Cost Evaluation Function

摘要

This paper describes a unique and optimal method for realtime global path planning and collision avoidance for navigation of a mobile robot in complex time varying environments. Occupancy based 3D grid map and Gaussian distribution model based obstacle prediction are employed to represent the dynamic environment. Path planning and obstacle avoidance are performed by applying a cost-evaluation function on time-space Distance Transforms to uniquely produce the optimal path at the time of planning. Experimental results are presented verifying the effectiveness and versatility of the algorithm in both predictable and imperfectly predictable time varying environments.