• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2026, Vol. 62 ›› Issue (3): 366-383.doi: 10.3901/JME.260091

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External Force Estimation Method for Force Sensorless Industrial Robots with High Anti-interference

GUO Wanjin1,2,3, LI Qianhui1, XU Mingkun1, HOU Xudong1, LIU Xiaoheng1, CAO Chuqing2,4, ZHAO Lijun2,5   

  1. 1. Key Laboratory of Road Construction Technology and Equipment, Ministry of Education, Chang'an University, Xi'an 710064;
    2. Yangtze River Delta HIT Robot Technology Research Institute, Wuhu 241007;
    3. EFORT Intelligent Robot, Co., Ltd., Wuhu 241060;
    4. School of Computer and Information, Anhui Polytechnic University, Wuhu 241000;
    5. Robotics Institute, Harbin Institute of Technology, Harbin 150001
  • Revised:2025-05-19 Accepted:2025-10-14 Published:2026-03-25
  • Supported by:
    国家自然科学基金面上项目(52275005)、陕西省自然科学基础研究计划资助(2025JC-QYXQ-027,2025JC-YBMS-619)、中央高校基本科研业务费专项资金(300102253201)、中国博士后科学基金(2024M760002)、安徽省机器视觉检测与感知重点实验室开放基金(KLMVI-2025-HIT-06)和长安大学高等教育教学改革研究项目(BZ202521)资助项目。

Abstract: To address the issues of external force estimation for industrial robots—namely, its dependence on accurate dynamic models, poor disturbance rejection, low estimation accuracy, and insufficient interpretability—an external force estimation method for force sensorless industrial robots with high anti-interference is proposed. Firstly, a dynamic model of a 5-degree-of-freedom industrial robot with a 3T2R configuration is established, considering the effects of joint friction torque and external forces. The nonlinear characteristics of joint friction are modeled using the Stribeck friction–velocity model. Secondly, an adaptive super-twisting sliding mode generalized momentum observer, with an adaptively tuned rate gain parameter, is then employed to estimate joint external torques. This approach improved estimation accuracy, reduced reliance on precise dynamic models, and enhanced interpretability. Thirdly, a mapping relationship between joint external torques and external forces is constructed using the Jacobian matrix, enabling external force estimation. Fourthly, comparative experiments are conducted against the adaptive super-twisting sliding mode observer, the super-twisting sliding mode observer, and the first-order generalized momentum observer. Taking Joint 1 as an example, the proposed method reduced the mean absolute error of joint external torque estimation by 12.9%, 39.9%, and 57.9%, respectively. Based on the established mapping, external forces are further estimated, demonstrating higher accuracy and validating the effectiveness of the proposed method. Finally, under the application of the same random disturbance, the proposed method is compared with the first-order generalized momentum observer. The root mean square error of the estimated joint external torque increased by only 1.5% for the proposed method, whereas it increased by 43.3% for the first-order method, verifying the superior disturbance rejection capability of the proposed method.

Key words: industrial robots, external force estimation, friction torque model, generalized momentum observer, super-twisting sliding mode

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