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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2026  > In Press, Accepted Manuscript
H. Liao, X. Wang, Z. Zhang, and N. Tan, “Model-free variable impedance control of redundant manipulators for soft tissue puncture,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 4, pp. 1–10, Apr. 2026. doi: 10.1109/JAS.2025.125693
Citation: H. Liao, X. Wang, Z. Zhang, and N. Tan, “Model-free variable impedance control of redundant manipulators for soft tissue puncture,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 4, pp. 1–10, Apr. 2026. doi: 10.1109/JAS.2025.125693
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Model-Free Variable Impedance Control of Redundant Manipulators for Soft Tissue Puncture

doi: 10.1109/JAS.2025.125693
Funds:  This work was supported by the National Natural Science Foundation of China (62173352) and the Guangdong Basic and Applied Basic Research Foundation (2024B1515020104)
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    Abstract
  • Robotic-assisted medical technology has long been a key area of research in modern surgical medicine. Robotic-assisted puncture techniques, both theoretically and practically, hold significant potential to improve puncture precision and overall surgical outcomes in clinical practice. This paper presents a model-free variable impedance control (MFVIC) method for robotic soft tissue puncture tasks, enabling high-precision puncture of soft tissues using variable impedance control without requiring model information. Conventional position- or force-based control methods often fail to ensure the precision of puncture or maintain an appropriate puncture force, both of which are critical for the task. The proposed variable impedance control approach allows for accurate puncture to the desired location while maintaining low puncture force throughout the puncture process, thus effectively meeting the demands of the puncture task. Additionally, a Jacobian matrix estimator is designed to estimate the Jacobian matrix of the redundant robotic arm in real-time during operation. This enables precise robot control using sensor data, without the need for prior knowledge of the robot model.

     

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