Compliant Human–Robot Collaboration with Accurate Path-Tracking Ability for a Robot Manipulator
Source abstract
Abstract
In this article, we aim to achieve manual guidance of a robot manipulator to perform tasks that require strict path following and would benefit from collaboration with a human to guide the motion. The robot can be used as a tool to increase the accuracy of a human operator while remaining compliant with the human instructions. We propose a dual-loop control structure where the outer admittance control loop allows the robot to be compliant along a path considering the projection of the external force to the tangential-normal-binormal (TNB) frame associated with the path. The inner motion control loop is designed based on a modified sliding mode control (SMC) law. We evaluate the system behavior to forces applied from different directions to the end-effector of a 6-DOF industrial robot in a linear motion test. Next, a second test using a 3D path as a tracking task is conducted, where we specify three interaction types: free motion (FM), force-applied motion (FAM), and combined motion with virtual forces (CVF). Results show that the difference of root mean square error (RMSE) among the cases is less than 0.1 mm, which proves the feasibility of applying this method for various path-tracking applications in compliant human–robot collaboration.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Teleoperation and Haptic Systems · Robot Manipulation and Learning · Soft Robotics and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical and Computer Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
Funding
Ministry of Science and Technology, Taiwan
References (38)
Show source-provided references
1. Rosenberg, L.B. (1993, January 18–22). Virtual fixtures: Perceptual tools for telerobotic manipulation. Proceedings of the IEEE Virtual Reality Annual International Symposium, Seattle, WA, USA.10.1109/VRAIS.1993.380795 ↗
2. Active constraints/virtual fixtures: A survey10.1109/TRO.2013.2283410 ↗
3. Haptic virtual fixtures for robot-assisted manipulation10.1007/978-3-540-48113-3_5 ↗
4. Restrepo, S.S., Raiola, G., Chevalier, P., Lamy, X., and Sidobre, D. (2017, January 3–7). Iterative virtual guides programming for human-robot comanipulation. Proceedings of the 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Munich, Germany.
5. Vision-assisted control for manipulation using virtual fixtures10.1109/TRO.2004.829483 ↗
6. Virtual fixtures with autonomous error compensation for human-robot cooperative tasks10.1017/S0263574709990415 ↗
7. Aspragathos, N.A., Koustoumpardis, P.N., and Moulianitis, V.C. (2019). Virtual Guides for Redundant Robots Using Admittance Control for Path Tracking Tasks. Advances in Service and Industrial Robotics, Springer International Publishing.10.1007/978-3-030-00232-9 ↗
8. Barri, M.H., Widyotriatmo, A. (2018, January 8–10). Path Reference Generation for Upper-Limb Rehabilitation with Kinematic Model. Proceedings of the 2018 IEEE International Conference on Robotics, Biomimetics, and Intelligent Computational Systems (Robionetics), Bandung, Indonesia.10.1109/ROBIONETICS.2018.8674676 ↗
9. Guidance-control-based exoskeleton rehabilitation robot for upper limbs: Application to circle drawing for physiotherapy and training10.5405/jmbe.1663 ↗
10. Zhao, Y., Liang, C., Gu, Z., Zheng, Y., and Wu, Q. (2020). A new design scheme for intelligent upper limb rehabilitation training robot. Int. J. Environ. Res. Public Health, 17.10.3390/ijerph17082948 ↗
11. Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications10.1016/j.mechatronics.2018.02.009 ↗
12. Active compliant motion: A survey10.1163/156855305323383767 ↗
13. High-accuracy robotized industrial assembly task control schema with force overshoots avoidance10.1016/j.conengprac.2017.10.015 ↗
14. Collaborative manufacturing with physical human-robot interaction10.1016/j.rcim.2015.12.007 ↗
15. Peng, Y.C., Chen, S., Jivani, D., Wason, J., Lawler, W., Saunders, G., Radke, R.J., Trinkle, J., Nath, S., and Wen, J.T. (2021). Sensor-Guided Assembly of Segmented Structures with Industrial Robots. Appl. Sci., 11.10.3390/app11062669 ↗
16. Tsumugiwa, T., Yokogawa, R., and Hara, K. (2002, January 11–15). Variable impedance control based on estimation of human arm stiffness for human-robot cooperative calligraphic task. Proceedings of the 2002 IEEE International Conference on Robotics and Automation, Washington, DC, USA.
17. Training children aged 5–10 years in manual compliance control to improve drawing and handwriting10.1016/j.humov.2018.04.002 ↗
18. Ravankar, A., Ravankar, A.A., Kobayashi, Y., Hoshino, Y., and Peng, C.C. (2018). Path smoothing techniques in robot navigation: State-of-the-art, current and future challenges. Sensors, 18.10.3390/s18093170 ↗
19. Hsiao, T., and Huang, P.H. (2017). Iterative Learning Control for Trajectory Tracking of Robot Manipulators. Int. J. Autom. Smart Technol., 7.10.5875/ausmt.v7i3.1410 ↗
20. Co-manipulation with a library of virtual guiding fixtures10.1007/s10514-017-9680-7 ↗
21. Reference Trajectory Reshaping Optimization and Control of Robotic Exoskeletons for Human-Robot Co-Manipulation10.1109/TCYB.2019.2933019 ↗
22. Steady-hand robotic system for microsurgical augmentation10.1177/02783649922067807 ↗
23. Safe and intuitive manual guidance of a robot manipulator using adaptive admittance control towards robot agility10.1016/j.rcim.2021.102127 ↗
24. Adaptive Sliding Mode Control for Robotic Surface Treatment Using Force Feedback10.1016/j.mechatronics.2018.04.008 ↗
25. Variable Structure Control: A Survey10.1109/41.184817 ↗
26. Chattering reduction of sliding mode control by low-pass filtering the control signal10.1002/asjc.195 ↗
27. A survey of applications of second-order sliding mode control to mechanical systems10.1080/0020717031000099010 ↗
28. Design and experimental validation of a second-order sliding-mode motion controller for robot manipulators10.1080/00207170802112591 ↗
29. Integral Sliding Mode Control: Performance, Modification, and Improvement10.1109/TII.2017.2761389 ↗
30. Wang, P.H. (2019). Comparisons of a Novel Low Chattering Sliding Mode Control and Other Sliding Mode Controls with Application to Trajectory Tracking of a 6-Axis Robot Manipulator. [Master’s Thesis, National Chiao Tung University].
31. Lecours, A., Mayer-St-Onge, B., and Gosselin, C. (2012, January 14–18). Variable admittance control of a four-degree-of-freedom intelligent assist device. Proceedings of the 2012 IEEE International Conference on Robotics and Automation, Saint Paul, MN, USA.10.1109/ICRA.2012.6224586 ↗
32. Variable Impedance Control of Redundant Manipulators for Intuitive Human-Robot Physical Interaction10.1109/TRO.2015.2430053 ↗
33. Reyes-Uquillas, D.A., and Hsiao, T. (2017, January 12–15). Online motion adjustment using compliance control for a multi-axis robot manipulator. Proceedings of the 2017 International Automatic Control Conference (CACS), Pingtung, Taiwan.10.1109/CACS.2017.8284253 ↗
34. Manipulator performance constraints in human-robot cooperation10.1016/j.rcim.2017.09.015 ↗
35. International Organization for Standardization (2016). ISO/TS 15066:2016, International Organization for Standardization.
36. Measurement of unidirectional pose accuracy and repeatability of the collaborative robot UR5
37. Testing of an industrial robot’s accuracy and repeatability in off and online environment10.17531/ein.2018.3.15 ↗
38. Off-line scan path planning for robotic NDT10.1016/j.measurement.2018.02.020 ↗