Dynamic picking and obstacle avoidance path planning of coal gangue sorting robot

In order to solve the problems that the coal gangue sorting robot cannot avoid large obstacles in real time, the efficiency of picking coal gangue is low, and the vibration and shock will be generated when grasping target gangue, the limitations of the traditional intercepting method of picking up coal gangue and the applicability of the dynamic programming algorithm to coal gangue sorting robots are analyzed, and a dynamic obstacle avoidance path planning algorithm suitable for coal gangue sorting robots is proposed.Firstly, this algorithm introduces relative speed and relative acceleration into the potential field function based on the traditional artificial potential field method.The potential field force acting on the coal gangue sorting robots drives the robot to reach the target gangue position, and tends to keep consistent with the movement of gangue, so that the coal gangue sorting robot has the capability of dynamic obstacle avoidance, the capability to adapt to variable-speed belt transportation.Then aiming at the end position constraint of belt conveyor to the coal gangue sorting robot, a height constraint is introduced into the potential field function.The potential field force drives the coal and gangue sorting robot to avoid the belt conveyor during the obstacle avoidance path planning, which ensures the rationality and safety of the robot movement.Finally, the simulation and robot experiment results show that the algorithm can realize the dynamic obstacle avoidance picking of coal gangue by sorting robot, meet the position constraints of the belt conveyor to the robot.When the robot reaches the position of gangue, the relative velocity and acceleration are zero, that is, the robot and the target gangue have the same movement trend, and there will be no vibration and shock during the gangue grasping.In the comparative experiment with the traditional artificial potential field method, the applicability and superiority of the proposed algorithm for the coal gangue sorting robot are verified.