A suboptimal path planning algorithm using rapidly-exploring random trees

This paper presents path planning algorithms using Rapidly-exploring Random Trees (RRTs) to generate paths for unmanned air vehicles (UAVs) in real time, given a starting location and a goal location in the presence of both static and pop-up obstacles. Generating near optimal paths in obstacle rich environments within a given short time window is a challenging task. Hence we first generate a path quickly using RRT by taking the kinematic constraints of the UAV into account. Then we develop an anytime algorithm that yields paths whose quality improves as computation time increases. When the UAV detects a pop-up obstacle the path planner re-generates a new path from its current location. In order to track a generated path, an effective guidance law with a switching mechanism based on pursuit and line of sight guidance laws is developed. Simulation studies are carried out to demonstrate the performance of the proposed algorithm.

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