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Improved RRT Path Planning Algorithm Based on Obstacle Boundary Heuristics

RRT algorithm is widely used in RoboCup small size league competitions for its simplicity and quickness. As this algorithm has many search points, lacks stability and is quite deviated from the optimal solution, this paper provides an improved RRT path planning algorithm based on obstacle boundary heuristics, which explores the random tree toward the target points, obstacle boundary points and random points based the self-adaptation probability. The author performed RRT and the performance test of this algorithm based on a number of obstacle boundary models. Experiments show that this algorithm has quite concentrated distribution of time consumed, which is more likely to meet the timeliness requirement, and the path generated is closer to the optimal result.