Path Planning Technology Of Indoor Mobile Robot

With the development of intelligent technology,mobile robots with autonomous navigation are widely used in driverless,storage and transportation,intelligent inspection and other fields.To perform various complex tasks autonomously,mobile robots need to have three core capabilities of mapping and positioning,path planning and motion control.Therefore,this paper aims to improve the global and local path planning algorithm to realize autonomous navigation with lid ar as the main sensor.The research contents of this paper incl ude the following four parts:(1)Aiming at the shortcomings of A* and Hybrid A* algorithms,a piecewise global path planning algorithm based on motion constraints is proposed.First,the path points of the A* algorithm are moved and deleted,and the key turning points are retained.Then,the pose penalty is used to calculate the node expansion.Finally,the key points are used as the target points to guide the Hybrid A* algorithm to perform secondary path planning in segments.The simulation results show t hat the path planned by the improved algorithm has continuous curvature,and the turning point is reduced by 75%,which makes the robot move smoothly and efficiently.(2)To solve the problem that the DWA(Dynamic Window Approach)algorithm has a local optimal solution,the evaluation of the global path is added to the trajectory evaluation function to improve the global optimality of the obstacle avoidance path.The simulation results show that the improved algorithm is effective and real-time in obstacle avoidance.(3)Using a mobile chassis with a four-wheel differential motion structure and a 16-line lidar,the hardware construction and algorithm configuration of the autonomous navigation system are completed based on ROS(Robot Operating System)software.(4)The indoor environment map is established to test the navigation function,and the global path planning experiment is carried out in the static map.When the robot is moving,lidar is used to detect obstacles in real-time,and the function of local obstacle avoidance path planning is tested in a dynamic environment.The experimental results show that in different environments,the mobile robot can stably complete the autonomous navigation task,in which the global path length is reduced by 9.4 % on average,the moving time is reduced by 12.3% on average,and it can flexibly avoid obstacles in dynamic environments.The algorithm meets the working requir ements of autonomous navigation.