A Pendulum Approach to Understanding the Dynamics of Transient Contact in Human-Robot Collaboration
The integration of collaborative robots (Cobots) into various fields is increasingly observed, and the importance of ensuring safety in human-robot interactions (HRI) is thereby underscored. The critical aspect of transient contact dynamics, a fundamental yet under-explored area in HRI safety, is addressed in this paper. Unlike quasi-static contacts, transient interactions involve brief, dynamic impacts that pose unique challenges for safety assessments and Cobot behaviour modulation. In this paper, a novel approach to studying these interactions is introduced, employing a customizable pendulum experimental setup that simulates transient contact scenarios. Additionally, a comprehensive model for calculating the equivalent mass of robots is developed, aiming at improving the simplified model currently proposed by ISO/TS 15066. The robot’s configuration and the direction of impact are incorporated into this model, providing a more nuanced understanding of the forces at play during contact. A series of experiments demonstrates the relationship between impact forces, robot velocity, and the simulated mass of human body parts. These insights are deemed useful for the design of Cobots to minimize the risk of injury in a shared workspace.
Authors
- Giovanni Legnani (ORCID: https://orcid.org/0000-0002-2700-5093)
- Irene Fassi (ORCID: https://orcid.org/0000-0002-6144-2123)
- Marcello Valori (ORCID: https://orcid.org/0000-0003-4663-9865)
- David Vetturi (ORCID: https://orcid.org/0000-0002-1798-7935)
- Sadeesha Samarathunga
- Roberto Pagani (ORCID: https://orcid.org/0000-0002-3686-5351)
- Andrea Bertagna
Institutions
- National Agency for New Technologies, Energy and Sustainable Economic Development (IT)
- Tecnologie Avanzate (Italy) (IT)
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing
- University of Brescia (IT)
Publication Details
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1109/mesa61532.2024.10704881
- Citations
- 1
- Primary Topic
- Robot Manipulation and Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.33