Dynamic continuous simulation study of robotic arms for human-machine shared control

ObjectiveThe human-machine shared control is widely used in the remote control of robots as a control method that combines the operator’s judgmental decisions with the fine control of the robotic arm. When the control weight of the robotic arm is switched, the joint angle changes abruptly due to the composition of the robotic arm, signal delay and other reasons, which affects the dynamic continuity of the control system.MethodsTo solve this problem, a feasible shared control strategy was proposed to determine the control weight, a local fitting algorithm based on the interpolation of 3 times Bezier curves was used to realize the optimization of the trajectory of the robotic arm, and the continuity of the control system of the robotic arm was simulated and verified with respect to the optimized trajectory of this algorithm.ResultsThe simulation results show that by comparing different trajectory planning curves, the adopted method can effectively inhibit the sudden change of the angle caused by the switching of control weights, realize the continuous smoothing of the joint angle and angular velocity curves at the switching moment, and effectively inhibit the acceleration oscillations, which has good robustness.