To overcome the shortcomings of the traditional artificial potential field method in mobile robot path planning,an improved method was proposed,in which potential field intensity was used instead of force vector to plan the path for the mobile robot. By addition of coefficient item to repulsion potential field of obstacles, the destination unreachable problem caused by the closely distance between destination and obstacles was solved. Considering the speed-effect of mobile obstacles and mobile robot,the velocity information was introduced into potential field function and an"added potential field"was also introduced to guide the robot to be out of local minimum points. Based on the new method,all the potential field intensity was added by algebraic sum style,then the genetic trust region algorithm was used to search the minimum sum point of potential field intensity within the movement scope which the robot can arrive at during a sampling period,and the global optimization path was composed of all the minimum points. Experiment results show that better path planning for mobile robot in dynamic environment can be achieved by this new method.