This paper proposes a new path planning strategy - the Rapid Visible Tree (RVT) algorithm to guide a robot to its goal in a complex environment without dangerous collisions. By fusing the visibility information with the classic tree-based searching method, RVT only takes the noisy points locally acquired from the environment as input and computes the visible region at each location to decide the growing direction of the path tree. Compared with traditional methods, RVT is more efficient, lightweight, and robust. We demonstrate that the RVT algorithm can not only complete the path planning task in real-time but also explore the unknown environment in simulated or real scenes.
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