A novel algorithm, which comprises with convex hull construction algorithm and robot controller is proposed for robot path planning based on complicated local data in robot’s autonomous navigation system. First the algorithm searches out the local optimal path from the robot’s current position to its target according to the local obstacle data. When the robot can not reach the final target directly, a temporary target point in the optimal path will be set to instruct the robot to avoid the obstacle and reach the final target. Next, a controller is design based on attractive force field and repulsive force field to control the robot’s motion, the combined effect of both attractive force field and repulsive force field drives the robot move toward the objective acquired from the optimal path and avoid obstacles at the same time. The experiment results show that this method can provide a better planning path compared with traditional path planning algorithms such as artificial potential field (APF), the wall-following (Bug) and the artificial moment method, and it has a fast reaction speed that is suitable for practical applications.