The BITO-RRT* (Bidirectional traversal optimization RRT*) algorithm is proposed to solve the problem of insufficient planning stability under different environments when the robot global path planning algorithm must increase the convergence rate. Firstly

the bidirectional growth strategy of target bias and direct detection is introduced to accelerate the convergence rate and obtain the initial solution. Then the direct path is optimized by traversal optimization step. Finally

the parent node is reselected in the asymptotic convergence region to shorten the path length and smooth the path. In different complexity environments

BITO-RRT* algorithm compared with RRT

RRT* and Informed-RRT* three algorithms

all showed excellent comprehensive performance

and the path planning success rate of 4 types of algorithms in complex environments was 90%

55%

57% and 58% respectively. It is proved that the BITO-RRT* algorithm not only improves the path convergence speed

but also has better path quality and planning stability than other algorithms under limited sampling times.