A path planning method for mobile robots with energy consumption optimization
In order to achieve real-time obstacle avoidance and global optimal path planning for mobile robots with limited energy,a path planning method combining improved A*algorithm and improved dynamic window method and considering energy consumption was proposed.Firstly,by considering factors such as ground slope and friction,a mobile robot energy consumption model was established and the A*evaluation function was optimized.The globally optimal path was planned while balancing the shortest distance and minimum energy consumption.Secondly,the searching efficiency was improved by increasing the A*searching neighborhood and optimizing the A*searching direction.The collinear point principle was used to remove redundant nodes,and key nodes were extracted as sub-target points for the improved dynamic window method.Finally,in response to the problem of poor flexibility of the dynamic window method in complex environment,mobile robot size information was introduced,and the distance between the mobile robot contour and obstacles was used as the collision constraint influencing factor.The minimum turning radius constraint was added to ensure that the mobile robot can move more accurately without collision.The simulation experiment results show that,the proposed fusion path planning method can reduce energy consumption by 43.88％compared with the traditional A*algorithm,and the robot can effectively avoid obstacles and move more smoothly in dynamic environments.
path planningA* algorithmdynamic window methodoptimal energy consumption
万方数据
维普
