Abstract
Precise manipulation in dynamic environments, whether induced by a mobile robot base or a target with unknown motion, remains a major challenge in robotics. Manipulation in dynamic environments introduces substantial uncertainty, which fundamentally conflicts with the tight precision requirement of precise tasks such as peg-in-the-hole. We propose a Vision-Force Admittance Learning (VFAL) framework that fuses asynchronous visual feedback with a high-frequency force-based model, using visual pose estimations as a regularization term. VFAL adapts insertion strategies online to dynamic motion while maintaining millimeter-level precision. To obtain robust, low-frequency pose information, we employ state-of-the-art vision foundation models for visual pose estimation. Additionally, we incorporate failure recovery mechanisms to enhance overall robustness. We validate our approach in real-world experiments, demonstrating high success rates and strong adaptability to various pegs and dynamic environments.
Keywords
Publication details
- Journal
- Not available
- Open access
- Green open access
Cite this article
APA 7
Chen, Y., Liang, Y., Xu, Y., Fang, I., Kidder, C., Wang, H. P., Haque, R., Zhang, Y., & Feng, C. (2026). Vision-Force Admittance Learning for Peg Insertion into a Movable Hole. https://omanscience.com/en/articles/vision-force-admittance-learning-for-peg-insertion-into-a-movable-hole
MLA 9
Chen, Yuzhong, et al. "Vision-Force Admittance Learning for Peg Insertion into a Movable Hole." https://omanscience.com/en/articles/vision-force-admittance-learning-for-peg-insertion-into-a-movable-hole.
Chicago (author–date)
Chen, Yuzhong, Yongqing Liang, Yunzhi Xu, Irving Fang, Chase Kidder, Hui-ping Wang, Raihan Haque, Yubiao Zhang, and Chen Feng. 2026. "Vision-Force Admittance Learning for Peg Insertion into a Movable Hole." https://omanscience.com/en/articles/vision-force-admittance-learning-for-peg-insertion-into-a-movable-hole.
Harvard
Chen, Y., Liang, Y., Xu, Y., Fang, I., Kidder, C., Wang, H. P., Haque, R., Zhang, Y. and Feng, C. (2026) 'Vision-Force Admittance Learning for Peg Insertion into a Movable Hole', Available at: https://omanscience.com/en/articles/vision-force-admittance-learning-for-peg-insertion-into-a-movable-hole.
Vancouver
Chen Y, Liang Y, Xu Y, Fang I, Kidder C, Wang HP, et al. Vision-Force Admittance Learning for Peg Insertion into a Movable Hole. https://omanscience.com/en/articles/vision-force-admittance-learning-for-peg-insertion-into-a-movable-hole
IEEE
Y. Chen, Y. Liang, Y. Xu, I. Fang, C. Kidder, H. P. Wang, R. Haque, Y. Zhang, and C. Feng, "Vision-Force Admittance Learning for Peg Insertion into a Movable Hole," https://omanscience.com/en/articles/vision-force-admittance-learning-for-peg-insertion-into-a-movable-hole.