Near Time-Optimal Trajectories with ISO Standard Constraints for Human–Robot Collaboration in Fabric Co-Transportation

Enabling robots to work safely close to humans requires both adherence to safety standards and the development of appropriate strategies to plan and control robot movements in accordance with human movements. Collaboration between humans and robots in a shared environment is a joint activity aimed at completing specific tasks, requiring coordination, synchronisation, and sometimes physical contact, in which each party contributes its own skills and resources. Among the most challenging tasks of human–robot cooperation is the co-transport of deformable materials such as fabrics. This paper proposes a method for generating the trajectory of a collaborative manipulator. The method is designed for the co-transport of materials such as fabrics. It combines a near time-optimal control strategy that ensures responsiveness in following human actions while simultaneously guaranteeing compliance with the safety limits imposed by current regulations. The combination of these two elements results in a viable co-transport solution which preserves the safety of human operators. This is achieved by constraining the path of the robot trajectory with prescribed velocities and accelerations while simultaneously ensuring a near time-optimal control strategy. In short, the robot movement is generated in such a way as to ensure both the tracking of humans in the co-transportation task and compliance with safety limits. As a first attempt to adopt the proposed approach to integrate time-optimal strategies into human–robot interaction, the simulations and preliminary experimental result obtained are promising.

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Publication Details

Journal
Robotics
Published
2025-01-27
DOI
https://doi.org/10.3390/robotics14020010
Citations
4
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
4.86

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article

Near Time-Optimal Trajectories with ISO Standard Constraints for Human–Robot Collaboration in Fabric Co-Transportation

Andrea Bonci, Renat Kermenov, Sauro Longhi, Alessandro Di Biase et al.
4 citations
Robotics
Robot Manipulation and Learning
4.86
article

Near Time-Optimal Trajectories with ISO Standard Constraints for Human–Robot Collaboration in Fabric Co-Transportation

Andrea Bonci, Renat Kermenov, Sauro Longhi, Alessandro Di Biase, Ilaria Pellicani
article en
4 citations

Abstract

Enabling robots to work safely close to humans requires both adherence to safety standards and the development of appropriate strategies to plan and control robot movements in accordance with human movements. Collaboration between humans and robots in a shared environment is a joint activity aimed at completing specific tasks, requiring coordination, synchronisation, and sometimes physical contact, in which each party contributes its own skills and resources. Among the most challenging tasks of human–robot cooperation is the co-transport of deformable materials such as fabrics. This paper proposes a method for generating the trajectory of a collaborative manipulator. The method is designed for the co-transport of materials such as fabrics. It combines a near time-optimal control strategy that ensures responsiveness in following human actions while simultaneously guaranteeing compliance with the safety limits imposed by current regulations. The combination of these two elements results in a viable co-transport solution which preserves the safety of human operators. This is achieved by constraining the path of the robot trajectory with prescribed velocities and accelerations while simultaneously ensuring a near time-optimal control strategy. In short, the robot movement is generated in such a way as to ensure both the tracking of humans in the co-transportation task and compliance with safety limits. As a first attempt to adopt the proposed approach to integrate time-optimal strategies into human–robot interaction, the simulations and preliminary experimental result obtained are promising.

RoboticsVol. 14(2)
Marche Polytechnic University (IT), Polytechnic University of Bari (IT)
European Commission, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 6%
Robot Manipulation and Learning
4.86
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