[1]WAN Lihong,LIN Jie,LIU Na,et al.Force-controlled robotic polishing of curved surfaces with 3D vision[J].CAAI Transactions on Intelligent Systems,2026,21(2):444-452.[doi:10.11992/tis.202506024]
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Force-controlled robotic polishing of curved surfaces with 3D vision

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 21 Number of periods: 2026 2 Page number: 444-452 Column: 学术论文—机器人 Public date: 2026-05-16
Title:
Force-controlled robotic polishing of curved surfaces with 3D vision
Author(s):
WAN Lihong1;  LIN Jie1;  LIU Na2;  ZHANG Zeyang1;  WU Guodong1;  JIANG Yuandong1
1. Origin Dynamics Intelligent Robot Co., Ltd, Zhengzhou 450046, China;
2. University of Shanghai for Science and Technology, Institute of Machine Intelligence, Shanghai 200093, China
Keywords:
3D vision; six-axis force sensor; force control; curved surface polish; hierarchical control; curvature-driven; admittance control; manipulator
CLC:
TP242
DOI:
10.11992/tis.202506024
Abstract:
To address the issues of over-grinding and under-grinding caused by the interaction between geometric inaccuracies and contact forces in complex surface grinding, this study proposes a vision-guided and six-dimensional force-controlled collaborative adaptive grinding method for robotic arms. The system collects real-time point cloud data of the workpiece surface using a 3D structured light camera to generate the initial grinding trajectory, while a six-dimensional force sensor acquires contact force/moment information to dynamically adjust the end-effector pose for compensating surface geometric deviations. A hierarchical control architecture is adopted to achieve collaboration between global vision-based trajectory planning and local force-controlled fine-tuning. Torque feedback is utilized to suppress tool slippage and improve surface conformity. Additionally, virtual stiffness is adjusted online based on point cloud curvature to avoid overload. In grinding experiments on complex curved workpieces, compared to methods relying solely on visual trajectory tracking or force control, this study significantly reduces Ra to 0.8 μm, decreases force tracking error by 62%, and effectively eliminates contact loss caused by initial pose deviations.
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