Path planning is an indispensable technology in the field of robot research. Aiming at the path planning problem of mobile robot in complex unknown environment, an improved RRT_Connect algorithm is proposed to optimize the searched nodes and planned partial paths. Firstly, the algorithm introduces bias strategy of endpoint and searched node, which introduces bias probability reference value of endpoint and searched node in random sampling function, so that random sampling point is set as endpoint or searched node according to random probability. Then, by screening the effective new nodes and the parents of neighboring nodes in a certain range, the path planning cost is optimized to make the planned path tend to be smooth. The simulation results show that the path planned by the proposed improved RRT_Connect algorithm is better than before in terms of the average number of turns, average planned path length and average planning success rate.

RRT_Connect algorithm  /  mobile mobot  /  path planning  /  goal biased strategy