A rapid path planner for autonomous ground vehicle using section collision detection

Abstract

Rapid path planner plays an important role in autonomous ground vehicle (AGV) operation. Depending on the non-holonomic kinematics constraints of AGV, its path planning problem is discussed. Since rapidly-exploring random tree (RRT) can directly take non-holonomic constraints into consideration, it is selected to solve this problem. By applying extra constraints on the movement, the generation of new configuration in RRT algorithm is simplified and accelerated. With section collision detection method applied, collision detection within the planer becomes more accurate and efficient. Then a new path planner is developed. This method complies with the non-holonomic constraints, avoids obstacles effectively and can be rapidly carried out while the vehicle is running. Simulation shows that this path planner can complete path planning in less than 0.5 s for a 170 m×170 m area with moderate obstacle complexity.

A Bi-Level Path Planning Algorithm for Multi-AGV Routing Problem

“…Alex, C et al [10] used a method based on Voronoi graph to solve AGV path planning. Zhe, L et al [11] improved RRT (rapidly-exploring random trees) method with arc approximation collision detection, which aims to finish local path planning fast enough to satisfy real-time tasks.…”