Improved whale algorithm and its application in cobot excitation trajectory optimization

The improved whale algorithm is proposed to design the excitation trajectory in the parameter identification of collaborative robots. Firstly, the whale algorithm is improved, the initial population is optimized by the method of uniform distribution, the adaptive weight is introduced to enhance the optimization ability of the algorithm, and the optimization speed of the algorithm is improved by using the convergence factor. Then establish the dynamic model of the robotic arm, design the excitation trajectory of the collaborative robot, and use the improved whale algorithm to optimize the excitation trajectory. Finally, the HM06 robot is used as the experimental object to run the excitation trajectory optimized by the improved whale algorithm. The experimental results show that the excitation trajectory optimized by the improved whale algorithm is smooth and has strong anti-noise ability, which is beneficial to improve the accuracy of robot parameter identification.