A Research On Robot Path Planning Based On A Method Of Improved Artificial Potential Field

With the rapid development of social economy, the application of robots is becoming more and more widely used, and its field has expanded from traditional agriculture and industry into high-tech sectors such as services, sea and space exploration, nuclear industry, rehabilitation and military.Intelligent mobile robots use sensors to perceive the surrounding environment and position, and then compete the autonomous walking in the environment with obstacles and complete certain functions according to the requirement. Research on robot can be categorized into three sections:the mechanism of movement, motion control and navigation. Among them, path planning is one of the important tasks. Its task is to find a collision-free path from the starting point to the target point in an environment with obstacles. This paper will focus on the mobile robot path planning. The main research work can be summarized as follows:This paper firstly analysis the principle of artificial potential field path planning and the shortcomings of the artificial potential field. Then propose two improved measures on this basis. Firstly, introduced the distance between the mobile robot and the target point into repulsion function to construct a new repulsion function so that the robot stops when it reaches the target point; Second, put forward an escape force to the robot for the minimum problem in the traditional artificial potential field method, so that the robot will no longer stop at the local minima or do hovering motion, and can successfully reach the target position.Secondly, introduce the genetic algorithm into path planning. Using genetic algorithm obtain the more optimized parameters in the artificial potential field function to avoid local minima. To optimize the method of artificial potential field, this paper develops a method to change the pace dynamically according to the complexity of environments. In detail, the change of motion direction is calculated to decide how to calibrate the pace. This method can reduce the algorithm’s run time and avoid the local minimum.Finally, do large numbers of robot path planning simulation experiments based on the method of improved artificial potential field using MATLAB. Taking into account the actual situation of the robot operating environment, we need to consider the case of target movement and the movement of the obstacles in the path planning simulation study, then obtain the simulation results of the algorithm in dynamic environments.The simulation results show that the improved method can significantly overcome the shortcomings of traditional methods, thus verifying the effectiveness of the mobile robot path planning algorithm based on the method of improved artificial potential field.