The Study On Obstacle Avoidance Of Redundant Robot Based On The Improved Gradient Projection Method

The research on obstacle avoidance algorithm of redundant manipulator has always been one of the hotspots in the field of robot.But the current obstacle avoidance algorithm of redundant manipulator has some shortages,a closed loop control algorithm for obstacle avoidance based on the transformation of master and slave tasks is proposed aiming at the shortcomings of the traditional algorithm,and makes it more perfect and optimized.The main work and innovative results are as follows:1.The paper studies the localization of the obstacle,then obtains the coordinates of the obstacle by spatial point reconstruction method after image preprocessing about the obstacle,and it meets the requirements by the experiment of calibration plate.2.A closed loop control algorithm for obstacle avoidance based on the transformation of master and slave tasks is proposed aiming at the shortcomings of the algorithm for obstacle avoidance based on the gradient projection method.It achieves the switch of the task of obstacle avoidance and the task of the desired trajectory tracking by monitoring the minimum distance between the mechanical arm and the obstacle,thus it can solve the conflict between obstacle avoidance and desired trajectory tracking.When mechanical arms avoid obstacle,the end tracking accuracy is poor,based on this,the error control between the desired and actual end effector locations is introduced which makes the tracking accuracy significantly improved.In addition,the algorithm also has the advantages of small amount of computation and continuous variation of the velocity of escape and it can also be applied to collision avoidance of many obstacles and dynamic obstacle.3.The algorithm is verified by the simulation experiment of planar redundant robot with three degrees of freedom and physical experiment on UR5 experiment platform.The results show that the algorithm can effectively solve the conflict when the obstacle is on the desired tracking and the accuracy is high.It can also finish the obstacle avoidance of many obstacles and dynamic obstacle.