Robot Adaptive Grinding Planning and Steady State Tracking for Complex Surface

doi:10.3901/JME.260592

Abstract

Abstract: To solve the problem of difficult grinding trajectory planning and low force-position tracking accuracy for industrial robots on unknown curved surfaces, a grinding trajectory planning and force control method based on the generalized mapping of dynamic movement primitives (DMP) with trajectory generalization ability and adaptive impedance control algorithm is proposed. First, a singularity-free dynamic model of position and quaternion attitude for DMP is established, and the entire DMP system is extended to six dimensions by using the same clock system to drive motion synchronization. Then, the dynamic motion primitive is added to the DMP conversion system with the force coupling term derived from the adaptive impedance control, achieving force control capability while generalizing the trajectory to unknown curved surfaces, and the attitude correction algorithm is derived to track and correct the tool attitude when in contact with the surface. Finally, the proposed method is validated through simulations and physical experiments. The simulation results verify the tracking accuracy of the algorithm for generalized positions and its adaptability to trajectory variations. The experimental results demonstrate that the method not only accurately generalizes grinding trajectories on complex surfaces but also achieves satisfactory grinding performance on unknown surfaces, exhibiting strong practicality and stability.

Key words: dynamic movement primitives, unknown curved surfaces, grinding trajectory planning, adaptive impedance control

CLC Number:

TG156

QI Ruolong, REN Kang, ZHU Guang, ZHAO Jibin. Robot Adaptive Grinding Planning and Steady State Tracking for Complex Surface[J]. Journal of Mechanical Engineering, 2026, 62(11): 227-240.

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URL: http://www.cjmenet.com.cn/EN/10.3901/JME.260592

http://www.cjmenet.com.cn/EN/Y2026/V62/I11/227

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