In hybrid industrial environments, workers' comfort and positive perception of safety are essential requirements for successful acceptance and usage of collaborative robots. This paper proposes a novel human-robot interaction framework in which the robot behaviour is adapted online according to the operator's cognitive workload and stress. The method exploits the generation of B-spline trajectories in the joint space and formulation of a multi-objective optimisation problem to online adjust the total execution time and smoothness of the robot trajectories. The former ensures human efficiency and productivity of the workplace, while the latter contributes to safeguarding the user's comfort and cognitive ergonomics. The performance of the proposed framework was evaluated in a typical industrial task. Results demonstrated its capability to enhance the productivity of the human-robot dyad while mitigating the cognitive workload induced in the worker.

Robot Trajectory Adaptation to Optimise the Trade-off between Human Cognitive Ergonomics and Workplace Productivity in Collaborative Tasks

Marta Lagomarsino;Marta Lorenzini;Elena De Momi;Arash Ajoudani
2022-01-01

Abstract

In hybrid industrial environments, workers' comfort and positive perception of safety are essential requirements for successful acceptance and usage of collaborative robots. This paper proposes a novel human-robot interaction framework in which the robot behaviour is adapted online according to the operator's cognitive workload and stress. The method exploits the generation of B-spline trajectories in the joint space and formulation of a multi-objective optimisation problem to online adjust the total execution time and smoothness of the robot trajectories. The former ensures human efficiency and productivity of the workplace, while the latter contributes to safeguarding the user's comfort and cognitive ergonomics. The performance of the proposed framework was evaluated in a typical industrial task. Results demonstrated its capability to enhance the productivity of the human-robot dyad while mitigating the cognitive workload induced in the worker.
2022
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
978-1-6654-7927-1
Human Factors and Human-in-the-Loop
Human-Centered Robotics
Human-Robot Collaboration
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1233441
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