A Halton sequence fusion planning algorithm for HDRRT mobile robots

Aiming at the problem that the standard RRT algorithm (rapidly exploring random tree) using the pseudo-random sequence leads to uneven and unreasonable distribution of sampling points, and there are redundant sections and redundant nodes in the path of mobile robots from the starting point to the target point, a halton & dijkstra & rapidly exploring random tree(HDRRT) algorithm is proposed, which uses the Halton sequence with good uniform distribution of sampling points for sampling, and uses the candidate point set strategy to filter nodes to eliminate redundant nodes. At the same time, the improved Dijkstra algorithm is used to extract the key nodes of the original path to reduce the redundant path sections. On this basis, the path is smoothed by the cubic B-spline curve. The simulation results of the ROS system combined with Matlab show that the HDRRT algorithm has the advantages of rapidity, stable planning and smooth path compared with the Bias-RRT and standard RRT algorithm.