Local Minimum Research In Artificial Potential-field

Mobile robots are a kind of intelligent systems that can move and work autonomously in certain environment, and have been widely used in the area of industry, agriculture, daily life and military affairs. Navigation is the most fundamental and important problem for mobile robot and it is necessary for mobile robot to have the ability of moving around autonomously and safely. While the control methods based on robot learning is the key to achieve autonomous navigation.In this paper, propose a new method of collision free path planning in dynamic environment based on characteristics of flowing water, which integrates virtual water-flow with a potential-field based method to guide a mobile robot. This stored energy of position is referred to as potential energy. The robot's workspace is represented as a virtual terrain map (VTM) by the value of potential energy. In VTM,the place that is occupied by obstacles is higher and goal position is lower. And the artificial water-flows from high place to low place. There is artificial water head at initial position in the VTM. When artificial water reaches goal position in VTM, the robot will reach its goal position in the real world. The method has a low complexity and good real-time performance. The potential-field method coupled with virtual water-flow can also navigate a mobile robot in real time. Simulations and experiments show this algorithm possesses good performance, and can overcome the problem caused by local minimum and show the effectiveness and correctives of the method.