Kinematic Constrained Bi-directional RRT with Efficient Branch Pruning for robot path planning

•A novel Bi-directional RRT path planning scheme.•A local path planner taking into account the kinematic constraints.•An efficient branch pruning strategy.•The proposed KB-RRT* can achieve better performance in path planning. In this paper, we present a novel path planning algorithm called Kinematic Constrained Bi-directional Rapidly-exploring Random Tree with Efficient Branch Pruning (KB-RRT*), which is designed on the basis of Bi-directional Rapidly-exploring Random Tree (Bi-RRT) method. The KB-RRT* is suitable for path planning of a differential drive mobile robot. By incorporating the kinematic constraints, the KB-RRT* can avoid unnecessary growth of the tree and quickly find a feasible path for the agent. In addition, the proposed efficient branch pruning strategy helps the generated state find a better parent state and delete the edges with high cost around it. Therefore, the KB-RRT* achieves fast and high-quality path planning. The results of numerical simulations reveal that the proposed KB-RRT* can achieve better performance compared with the conventional path planning algorithms.