Because the rapidly-exploring random tree（ RRT） path planning algorithm is unstable and not optimal

propose a biased path search strategy which is called m-RRT. By generating a random point vectors to optimize the strategy of random points selection

the uncertainty of RRT searching can be improved

meanwhile

the expansion of searching tree can also be reduced. So

it can improve the searching speed to the destination

and the path got by m-RRT is better than that by RRT. Through the two-dimensional path planning and three-dimensional manipulator path planning

the results show that it has certain application value.