Abstract
This study introduces a method focusing on both obstacle avoidance and interaction techniques for a serial collaborative robot, employing impedance control. Collaborative robots operate in conjunction with humans within the same workspace, necessitating advanced control strategies to prevent human-robot collisions. The paper elaborates on an impedance control strategy that integrates force and position control, incorporating a virtual stiffness concept around objects. This approach facilitates not only the evasion of obstacles but also controlled interactions with objects when necessary. The efficacy of the proposed method is validated through numerical analyses, demonstrating its applicability in scenarios that demand both avoidance and intentional contact with objects.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Valigi, M.C., Logozzo, S., Canella, G.: A robotic 3D vision system for automatic cranial prostheses inspection. In: Ferraresi, C., Quaglia, G. (eds.) RAAD 2017. MMS, vol. 49, pp. 328–335. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-61276-8_36
El Zaatari, S., Marei, M., Li, W., Usman, Z.: Cobot programming for collaborative industrial tasks: an overview. Robot. Auton. Syst. 116, 162–180 (2019)
Hameed, A., Ordys, A., Możaryn, J., Sibilska-Mroziewicz, A.: Control system design and methods for collaborative robots. Appl. Sci. 13(1), 675 (2023)
Zhang, W., Cheng, H., Hao, L., Li, X., Liu, M., Gao, X.: An obstacle avoidance algorithm for robot manipulators based on decision-making force. Robot. Comput.-Integr. Manuf. 71, 102114 (2021)
Tian, H., Ma, X.: Behavioral dynamics-based impedance control for collision avoidance of human-following robots. In: 2022 IEEE International Conference on Real-time Computing and Robotics (RCAR), pp. 349–354. IEEE (2022)
Liao, Z., Wang, Y.: Trust-based variable impedance control of human-robot cooperative manipulation. Robot. Comput.-Integr. Manuf. 88, 102730 (2024)
Sasaki, M., Shibanoki, T., Tonooka, H.: Mobile robot control based on virtual impedance force feedback. In: 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), pp. 1–4. IEEE (2023)
Ding, Y., Thomas, U.: Improving safety and accuracy of impedance controlled robot manipulators with proximity perception and proactive impact reactions. In: 2021 IEEE International Conference on Robotics and Automation (ICRA), pp. 3816–3821. IEEE (2021)
Koutras, L., Vlachos, K., Kanakis, G.S., Dimeas, F., Doulgeri, Z., Rovithakis, G.A.: Enforcing constraints for dynamic obstacle avoidance by compliant robots. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 5221–5227. IEEE (2023)
Jiang, Y., Yang, C., Ju, Z., Liu, J.: Obstacle avoidance of a redundant robot using virtual force field and null space projection. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds.) ICIRA 2019. LNCS (LNAI), vol. 11740, pp. 728–739. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-27526-6_64
Roveda, L., Pedrocchi, N., Beschi, M., Tosatti, L.M.: High-accuracy robotized industrial assembly task control schema with force overshoots avoidance. Control Eng. Pract. 71, 142–153 (2018)
Engelbrecht, D., Steyn, N., Djouani, K.: Adaptive virtual impedance control of a mobile multi-robot system. Robotics 10(1), 19 (2021)
Acknowledgments
The research has been supported by the project PRIN 2022 PNRR - Unmanned rovers with applications to agricultural activities and soil sensing, CUP E53D23016900001.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Maddio, P.D., Sinatra, R., Cammarata, A. (2024). Impedance-Based Interaction Strategies for a Serial Collaborative Robot. In: Quaglia, G., Boschetti, G., Carbone, G. (eds) Advances in Italian Mechanism Science. IFToMM Italy 2024. Mechanisms and Machine Science, vol 163. Springer, Cham. https://doi.org/10.1007/978-3-031-64553-2_45
Download citation
DOI: https://doi.org/10.1007/978-3-031-64553-2_45
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-64552-5
Online ISBN: 978-3-031-64553-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)