Research On Path Planning And Tracking Technology Of Unmanned Vehicles In Complex Environments

Natural disasters such as earthquakes occur frequently in my country,and the existing disaster rescue methods are limited.Large-scale unmanned rescue platforms cannot reach the disaster site on time,and rescue equipment is not fully guaranteed,and there are problems such as low intelligence and difficulty in reaching.Life can’t be effectively guaranteed due to secondary disasters,so the research on the path planning and tracking technology of intelligent rescue equipment in complex environments has theoretical significance and practical value.This paper takes a certain type of 6×6 distributed drive unmanned platform as the research object,and mainly studies the current situation of unmanned rescue vehicles in complex environments,such as low intelligence,insufficient path planning and path optimization capabilities,etc.path tracking control,etc.:(1)A path planning algorithm suitable for complex environments is proposed:APF-guided RRT path planning algorithm-ARRT algorithm.The simulation experiments and comparative experiments of path planning in various complex environments are designed to verify the feasibility of the improved algorithm in dealing with path planning problems in complex environments.(2)Propose an APF-guided RRT path optimization algorithm.Solve problems such as path curve optimization after path planning.Make the optimized path curve continuous,smooth and smooth.(3)A model predictive control algorithm based on 6×6 distributed drive unmanned platform is proposed.The model predictive control algorithm is used to realize the tracking control of the optimized path curve by the unmanned platform.And four sets of simulation experiments are designed to verify the effectiveness of the algorithm for various complex path tracking control.(4)Taking a certain type of 6×6 distributed drive unmanned platform as the research object,the entire 6×6 distributed drive experimental platform was built,and the effectiveness of the above three algorithms in solving path planning and tracking control problems in complex environments was verified.feasibility.