Abstract
Robot force control performs better than position control in terms of dynamic and compliant control when interacting with complex environments. However, adding torque sensors to the robot’s joints or feet for precise torque control can significantly increase volume and weight. Furthermore, torque sensors are prone to be damaged during long-term robot walking, potentially making it impossible to control the robot. This paper proposes a method to estimate joint torque and ground reaction force for a one-legged hopping robot. The method involves analyzing the robot joint dynamics model, compensating for joint friction torque, and estimating joint torque. Nonlinear factors such as joint motor model errors and gearbox backlash can lead to errors in joint torque estimation. To address this issue, nonlinear errors are compensated through BP neural network training, resulting in more accurate estimation of joint torque. Based on the estimated joint torque, the ground reaction force is calculated. The effectiveness of the proposed method was verified by comparing external force measurement data during a one-legged hopping robot jumping to the ground with the estimated ground reaction force.
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References
Sayyad, A., Seth, B., Seshu, P.: Single-legged hopping robotics research—a review. Robotica 25(5), 587–613 (2007)
Zeng, G., Hemami, A.: An overview of robot force control. Robotica 15(5), 473–482 (1997)
Albu-Schaffer, A., Eiberger, O., Grebenstein, M., et al.: Soft robotics. IEEE Robot. Autom. Mag. 15(3), 20–30 (2008)
Albu-Schaffer, A., Ott, C., Hirzinger, G.: A unified passivity-based control framework for position, torque and impedance control of flexible joint robots. Int. J. Robot. Res. 26(1), 23–39 (2007)
Mehling, J.S., Strawser, P., Bridgwater, L., et al.: Centaur: NASA’s mobile humanoid designed for field work. In: IEEE International Conference on Robotics and Automation, pp. 2928–2933. IEEE, Piscataway, USA (2007)
Kawakami, T., Ayusawa, K., Kaminaga, H., Nakamura, Y.: High-fidelity joint drive system by torque feedback control using high precision linear encoder. In: IEEE International Conference on Robotics and Automation, pp. 3904–3909 (2010)
Zhang, H., Ahmad, S., Liu, G.: Torque estimation for robotic joint with harmonic drive transmission based on position measurements. IEEE Trans. Rob. 31(2), 322–330 (2015)
Pratt, J.E., Benjamin, T.K.: Series elastic actuators for legged robots. In: Unmanned Ground Vehicle Technology Vi, vol. 5422. SPIE (2004)
Haoyong, Y., Huang, S., Chen, G., Pan, Y., Guo, Z.: Human–robot interaction control of rehabilitation robots with series elastic actuators. IEEE Trans. Robot. 31(5), 1089–1100 (2015)
Li, X., et al.: Adaptive human–robot interaction control for robots driven by series elastic actuators. IEEE Trans. Robot. 33(1), 169–182 (2016)
Simpson, J.W.L., Cook, C.D., Li, Z.: Sensorless force estimation for robots with friction. In: Faculty of Informatics-papers, pp. 94–99 (2002)
Alcocer, A., Robertsson, A., Valera, A., Johansson, R.: Force estimation and control in robot manipulators. Ifac Proceedings Volumes 36, 55–60 (2003)
Albu-Schaffer, A., Hirzinger, G.: Parameter identification and passivity based joint control for a 7 DOF torque controlled light weight robot, In: Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No. 01CH37164), vol. 3. IEEE (2001)
Goh, A.T.C.: Back-propagation neural networks for modeling complex systems. Artif. Intel. Eng. 9(3), 143–151 (1995)
Pratt, J., Dilworth, P., Pratt, G.: Virtual model control of a bipedal walking robot. In: Proceedings of International Conference on Robotics and Automation, pp. 193–198 (1997)
Winkler, A., et al.: Path planning with force-based foothold adaptation and virtual model control for torque controlled quadruped robots. In: 2014 IEEE International Conference on Robotics and Automation (ICRA). IEEE (2014)
Pratt, J., Chew, C.-M., Torres, A., et al.: Virtual model control: an intuitive approach for bipedal locomotion. Int. J. Robot. Res. 20(2), 129–143 (2001)
Kalouche, S.: GOAT: A legged robot with 3D agility and virtual compliance. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4110–4117 (2017)
Acknowledgment
This work is supported by National Natural Science Foundation of China (Grants 52205034), “Pioneer” and “Leading Goose” R&D Program of Zhejiang (No. 2023C01177), Key Research Project of Zhejiang Lab (No. G2021NB0AL03), the National Natural Science Foundation of China (Grant No. 52205076).
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Zhou, W. et al. (2023). Joint Torque and Ground Reaction Force Estimation for a One-Legged Hopping Robot. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14271. Springer, Singapore. https://doi.org/10.1007/978-981-99-6495-6_45
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DOI: https://doi.org/10.1007/978-981-99-6495-6_45
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