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path planning plays an incomparable role in the application of indoor robot. In order to improve the convergence speed of path planning algorithm, and considering the time consumption and path quality, an improved RRT*( Rapidly Exploring Random Tree Star ) algorithm is proposed, aiming at the limitations of the algorithm. The algorithm adopts the purpose of setting instead of the original algorithm of random sampling gaussian sampling and the introduction of artificial potential field and obstacle avoidance strategy of combination of ideas, set up the target bias, guide the random tree growth direction, and then use the Manhattan distance to replace the Euclidean distance as the price valuation function, prevent a minimum loss of time and to a certain extent reduce algorithm. Experiments show that this method can effectively balance the convergence time and the reliability of the optimal path.