Research On Trajectory Optimization Of Industrial Robot After Preset Collision Avoidance Point

Aiming at the problems of low production efficiency,occasional mechanical collision and associated vibration in the process of loading and unloading of 6R joint robot,as well as the shortcomings of the basic whale optimization algorithm such as low convergence accuracy and easy to fall into local optimal solution,an improved whale optimization algorithm is proposed in this paper.Based on the improved algorithm,the motion analysis and trajectory planning of 6-DOF series industrial robot are studied.In this paper,the key technology of whale optimization algorithm improvement in the subject is studied,and the optimal trajectory planning of industrial robot is carried out.Firstly,the joint space coordinate system was established based on the standard D-H method,and then the forward and inverse kinematics were solved.The collision avoidance points were added before the path points to avoid mechanical collision,and the relevant parameters of each path point were calculated.Based on the Lagrange equation and MATLAB platform,the dynamic simulation experiments of the operation process with or without anti-collision points were carried out successively.After comparative analysis,the smooth and stable dynamic parameter curves of anti-collision points were obtained,which indicated that the anti-collision points added were effective.Simulation experiments were carried out on the workspace of the end-operator,and the results were compared to see whether the coordinates of different directions of the path points were satisfied.Then,the trajectory planning of the complete path with anti-collision points was carried out by using quintic polynomial interpolation.An improved whale optimization algorithm is proposed,that is,the nonlinear convergence factor is added and the inertia weight is introduced.The convergence performance of the improved algorithm is compared and analyzed,and then the time optimization of the traditional trajectory planning results is performed.The experimental results show that the total time of complete loading and unloading process after robot motion optimization is 20% to 50% shorter than that before optimization in practical application scenarios,which indicates that the improved WOA is effective,credible and of practical significance in the application of relevant fields.