Improved stable trajectory planning of the intelligent inspection robotic arm based on the Gray Wolf algorithm

The operating environment of the explosives repository inspection robot is complex, and there are many obstacles that seriously affect the stability of the operation of the robotic arm of the inspection robot. In order to ensure the stable operation of the robotic arm, a trajectory planning theory based on the improved gray wolf algorithm was proposed. In view of the disadvantages of the traditional gray wolf algorithm, with slow convergence speed and low optimization efficiency, the differential evolution algorithm, the population elimination evolution mechanism, and the standard gray wolf algorithm were fused to obtain a trajectory planning method suitable for intelligent inspection human manipulators. Then, four basis functions are used to compare the IGWO algorithm with the three other algorithms to ensure the reliability of the algorithm. Finally, the improved gray wolf algorithm is experimentally verified for the trajectory planning of the manipulator, which is compared with the traditional 3-5-3 polynomial trajectory optimization algorithm. The comparative experimental results show that the IGWO algorithm reduces the maximum joint acceleration of the robotic arm by 48.3% compared with the 3-5-3 polynomial optimization aspect, which improves the operational stability of the inspection robotic arm.