Research On Obstacle Avoidance Algorithm Based On Artificial Potential Field For Mobile Robots

Smart mobile robots are currently one of the most active areas for the development of science and technology.It plays an important role not only in service,industry,and agriculture,but also in the areas of urban security,aerospace,and military investigation.Therefore,smart mobile robots have attracted wide attention from various industries in the world.In the research field of robots,the navigation problem has attracted the interest of many scholars,and the path planning algorithm is a key technology for navigation problems of mobile robots.It ensures that the robot can safely reach the target point in a complex environment.In order to solve the problem of target unreachability and local minium value in the traditional artificial potential field method,the following work has been done:(1)In order to solve the target unreachable target in the traditional artificial potential field method,the repulsive potential field function in the traditional artificial potential field method is improved.In the traditional artificial potential field method,the distance between the robot and obstacles determines the size of the repulsive field.If there are no obstacles near the target point,the repulsion field will approach zero when the distance between the robot and the target point is reducing.Otherwise,the repulsion field will increase as the distance between the machine and obstacles decrease.In the light of the shortage,this paper add the euclidean distance between the mobile robot and the target point to repulsion potential field function,which ensures that the location of the target point is the minimum point of the global potential field.The effectiveness of the improved algorithm is proved by simulation.(2)In order to solve the problem of local minimum in traditional artificial potential field method,this paper proposes an obstacle connection method based on situational behavior.The situation in which the robot is trapped considers whether to connect multiple obstacles as a whole obstacle and add a virtual repulsion field to the local minimum region to help the robot escape from the local minimum region.The effectiveness of the improved algorithm is proved by simulation.