Path Planning for Mobile Robot Based on Improved RRT-Connect Algorithm
To solve the problems of high sampling randomness,poor target orientation,and low search effi-ciency in the path planning process of the bidirectional fast expanding random tree(RRT-Connect)algo-rithm,a region constrained sampling based RRT-Connect algorithm is proposed.Firstly,in the process of node expansion,the algorithm restricts the sampling points to the constraint area formed by the end of the other side′s search tree,to improve target orientation.At the same time,a reverse sub-sampling area is formed based on the area to escape local oscillations;Secondly,a variable steering angle strategy is con-structed to reduce the reverse growth phenomenon that occurs during the random sampling process;Finally,greedy strategy is used to eliminate redundant points in the path and second-order Bessel curve is used for path smoothing.Multiple simulation experiments have shown that the improved RRT-Connect algorithm has significant improvements in average path length,average planning time,and effective node utilization,which demonstrates the effectiveness of the improved mechanism.
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