Bidirectional Homotopy-Guided RRT for Path Planning

Abstract

As a popular robot path planning algorithm, RRT (Rapid-exploring Random Tree) and various RRT-based extensions have achieved remarkable results. However, existing algorithms rely too much on randomness and often do not make use of known map information, this makes the growth of trees too blind. To this end, we introduce Bidirectional Homotopy-Guided RRT (BH-RRT) that combines Bidirectional RRT (Bi-RRT) with information obtained from obstacle contours. Compared with the previous methods, BH-RRT can reflect most of the map's information with a small number of feature points, and then form a set of points. This set can provide a better local goal point in each iteration, so that the tree can grow in a more favorable direction, rather than only being affected by the goal point. Experimental results show that BH-RRT outperforms RRT, HRRT and Bi-RRT in the success rate within a limited time.