In Complex Environment Mobile Robot Research Path Planning Algorithm

With the progress of science,robot technology is rapidly integrated into human work and career.Mobile robot path navigation is one of the core intelligent technology in which Robot path planning technology is the most important part.The demand for mobile robot path planning technology is growing.The core content is that planning a collision-free path from the start to the target.The robot needs to meet the given constraints in the path planning algorithm,global and local path planning algorithms are adopted to deal with various complex environments.In view of all kinds of complex environmental constraints,many scholars have done a lot of research.But the plan time and path of the algorithm are still very long.This paper focuses on the path planning of mobile robots in complex environments.The kinematics basics and principles of mobile robots are introduced.At the same time,the parameters of the Raspberry Pi mobile robot are explained.(1)The RRT* path planning algorithm based on target guidance in complex environments is proposed to solve the problem of large randomness and long planning time in known environments.In dynamic environment,re-planning strategy is adopted on the target-based RRT* algorithm.Fuzzy reasoning strategy is proposed to solve the local deadlock problem in the presence of U-shaped obstacles.Finally,simulation experiments and Raspberry Pi robot experiments verify the effectiveness and feasibility of the algorithm.(2)The RRT algorithm planning path is not optimal and cannot cope with unknown environment.Therefore,the local path planning algorithm of A* two-way jump point with memory mechanism is proposed.The algorithm mainly solves the problems of long plan time and large amount of calculation for unknown environment.Before path planning,the two-way jump point strategy preprocesses the map.According to the selection rules,the two-way expansion of jump points that meet the rules are selected in the presence of obstacles and obstacles,which solves the above problems.In unknown environment,memory mechanism is introduced based on the A* two-way jump points algorithm.This mechanism requires the use of infrared sensors to detect the location of obstacles and memorize the current location.The re-planning task is completed by combining the intelligent corner strategy of fuzzy control and the strategy of gradually searching for sub-goals.Finally,simulation and Raspberry Pi robot experiments were carried out.The results verify the effectiveness and feasibility of the improved algorithm.