Research On Mobile Robot Path Planning And Autonomous Charging Technology

With the rise of the intelligent manufacturing industry,mobile robots have been widely used in power inspections,logistics distribution,indoor cleaning and other fields.The functions of mobile robots vary greatly in different scenarios,but long-term autonomous operation under unattended conditions is a major trend in the future.To achieve long-term autonomous operation of mobile robots,the key issue to be solved is the efficient,reliable and safe autonomous charging of mobile robots.According to the actual situation of the project,this paper proposes an improved ant colony algorithm that can quickly calculate a better path in a complex environment.The mobile robot quickly returns to the recognition range of the charging pile through the planned path,and proposes a charging based on the least squares method.Pile identification and positioning methods,a short-range docking strategy is proposed,which can realize the accurate docking of mobile robots and charging piles,and achieve the purpose of autonomous charging of mobile robots.The main contents of the research are:1.Propose the overall design plan of the mobile robot.Select appropriate hardware modules such as perception,execution,and power according to project requirements to build a mobile robot control system.Establish a two-wheel differential robot kinematics model to provide support for mobile robot trajectory planning,motion analysis,dynamics calculation,etc.,use ROS to build a mobile robot software system to provide a platform for mapping,positioning,navigation and other functions.2.Propose a path planning method based on improved ant colony algorithm.Ensure that the mobile robot quickly returns to the charging pile to identify the position when the battery is low.Aiming at the problems of slow convergence of basic ant colony algorithm,easy to fall into local optimum,and premature convergence,a heuristic function with target directivity is proposed,which can speed up the convergence speed of the algorithm.Simulation results show that the improved ant colony algorithm reduces the transfer of ants The blindness in the process improves the efficiency of target search.3.Propose the overall design plan of the autonomous charging system for mobile robots.According to the needs of the system,a power management module is designed to realize the real-time detection of power and trigger the autonomous charging process when the power is low.Completed the design of the docking hardware module,proposed a charging pile identification and positioning method based on the least squares method to achieve accurate identification and positioning of the charging pile,and designed a set of short-range docking strategies to improve the accuracy of the docking process.Ensure the accuracy of recognition and docking when the position is moved.4.Build a mobile robot autonomous charging experiment platform,design path planning and autonomous charging experiments.Experimental results show that the improved ant colony algorithm accelerates the path convergence speed and improves the quality of the path.The recognition method based on the least square method can effectively identify and locate the charging pile.The short-range docking strategy can realize the accurate docking of the mobile robot and the charging pile.The autonomous charging system can meet the requirements of autonomous charging for mobile robots.