Research On Obstacle Avoidance In Unknown Environment Under The Condition Of The Robot

As people’s living and working environment more and more complex and more uncertain factors in the case,among the practical use of robots in unknown environment how accurate and timely dodging obstacles becomes a hot and difficult research field of mobile robotics.Real time obstacle avoidance task is to successfully avoid all kinds of obstacles in the robot’s walking. This paper is based on the robot as experimental platform, introduced the development trend of robot in recent years and in the light of the research status and classification of various kinds of obstacle avoidance algorithms are briefly summarized. At the same time the principle and performance of the sensors will be used by the robot in the actual obstacle avoidance task and also the differences of various control strategies are introduced.In this paper, the basic principle and characteristics of the artificial potential field method is introduced, and the problems of the classical artificial potential field method are introduced, such as target non reachable, path oscillation, local minimum problem and the causes are analyzed in detail.And then, the position relationship between the robot and the target point is introduced into the repulsion function, and a new definition of attraction and repulsion, the problem of destination unreachable has been solved. Then the relative velocity between the robot and the target and the relative speed of the robot and the obstacle were introduced to the function of gravitational potential and repulsion in the improved, the robot encounters an obstacle or target point during the movement is poor sport avoidance performance issues is solved.Lastly, Aiming at the problem that the traditional artificial potential field method often appears in the narrow channel and the presence of large obstacles in the working environment of the robot, the obstacle avoidance is difficult, or some problems caused by one or more obstacles near the target point. The improved artificial potential field algorithm is used and the simulation experiment is carried out on the Matlab2014 platform and the validity of the improved method is verified, the robot successfully completed the obstacle avoidance task.