Path Planning For Mobile Robots Based On Voronoi Diagram And Uncertain Potential Field

Nowadays,with the gradual maturity of positioning and navigation technology,it is possible for mobile robots to navigate autonomously in unknown environments.But even the most advanced Simultaneous Localization and Mapping(SLAM)technology can introduce uncertainty to the location of obstacles in the map due to noise in the sensor.Typical path planning algorithms focus on how to reduce the uncertainty,and this paper will solve the uncertainty from another point of view.Aiming at the problem of uncertainty of environmental information,this paper proposes a path planning algorithm for mobile robots based on Voronoi uncertainty potential field,which enables mobile robots to navigate more carefully in uncertain environments.The main work and contributions of this paper are as follows:(1)In the aspect of global path planning,considering the uncertainty of global information,Voronoi diagram with higher path security is selected to model the path planning space.In the A* algorithm,considering the proportion of Predictive cost function in the evaluation function can affect the calculation time and accuracy of the algorithm.the dynamic coefficient is introduced.So that A* algorithm can guarantee both real-time and accuracy in global path planning.(2)In terms of local path planning,the obstacle uncertainty model is established,and the disadvantages of the APF(artificial potential field)algorithm are analyzed.By optimizing the APF algorithm and combining with the uncertainty of obstacles,the uncertain potential field is finally formed.The resultant force of the mobile robot in the potential field is taken as the control input of the robot to guide the robot to advance towards the local target point.(3)Combining the global and local path planning mentioned above,a mobile robot path planning algorithm based on Voronoi uncertainty potential field is proposed.The superior planner uses Voronoi diagram to model the planned space,and uses A*algorithm to traverse the nodes in the graph to ensure that the global path node set can be found.The inferior planner based on the uncertain potential field algorithm ensures that the mobile robot can keep a longer safe distance from the obstacle,and obtains a smooth path connecting the global path nodes.Through hierarchical division,the global path planning with high planning cost runs at a lower frequency,and the path is optimized according to the current environment information.Low-cost local path planning operates at a high frequency to ensure a timely response to changes in the position of obstacles.Finally,the simulation shows the Voronoi uncertain potential field can keep enough safe distance from obstacles in the uncertainty environment,and has good real-time performance.At the same time,it also proposes a new solution to the problem of information uncertainty when mobile robot navigates in unknown environment.