Research On Obstacle Avoidance Based On Embedded Mobile Robot

At this stage,the use of robots is increasingly being transferred from military sites to civilian sites,and the performance is gradually improving in continuous exploration.As a result,the popularity of mobile robots is getting higher and higher.It has been widely used in many wellknown industries and plays a very important role in many dangerous situations.After many years of exploration and research,a variety of path planning algorithms have been studied.Each path planning algorithm has its own advantages and disadvantages.Each algorithm has a specific use scene and the adaptability of the algorithm is not high when changing the scene.In view of this phenomenon,a hybrid obstacle avoidance algorithm based on artificial potential field method and fuzzy logic control algorithm for unknown environment is improved,and the obstacle avoidance algorithm is successfully transplanted into the embedded mobile robot.This paper focuses on obstacle avoidance algorithms for mobile robots in unknown environments.Through the analysis and comparison of several common obstacle avoidance algorithms.The hybrid obstacle avoidance algorithm based on artificial potential field method and fuzzy logic algorithm is adopted.Firstly,the artificial potential field method is studied,the advantages and disadvantages of the artificial potential field method are analyzed,and its shortcomings are improved.The local minimum problem of the artificial potential field method is solved by increasing the escape force,and the repulsive field function is modified to resolve the target unreachability problem.And then fuzzy logic control algorithm is introduced,whose advantages and disadvantages are analyzed.Combined with the advantage of artificial potential field method and the advantages of fuzzy logic algorithm,a hybrid algorithm based on artificial potential field and fuzzy logic is chosen.In order to prevent the mobile robot from choosing the optimal path in complicated environment,fuzzy logic control algorithm is used to provide sub-target points of each motion for the improved artificial potential field method,so that the robot can move to the target point mobile effectively,quickly and safely.Through MATLAB simulation,the effectiveness of the algorithm is verified.Based on the embedded mobile robot platform,the hybrid algorithm of artificial potential field method and fuzzy logic control algorithm is transplanted to the embedded mobile robot.And then,many experiments,including one single obstacle and multiple obstacle avoidance,are made in different environments respectively.The experimental results are analyzed and explained.The experimental results show that the embedded mobile robot moves stably in unknown environment,which can reach the target safely because of smooth path and good real-time performance.And the hybrid algorithm has a larger safety distance,more than 30%,from the obstacle than the original algorithm,which makes the mobile robot can reach the target point more safely.The feasibility of the hybrid obstacle avoidance algorithm for obstacle avoidance planning in unknown environment is verified.The research results of this dissertation provide a reference value for deeper research on obstacle avoidance algorithm,which also provide a reference for the transplantation of embedded mobile robot to obstacle avoidance algorithm.