The demand for safe and ergonomic workplaces is rapidly growing in modern industrial scenarios, especially for companies that intensely rely on Human-Robot Collaboration (HRC). This work focuses on optimizing the trajectory of the end-effector of a cobot arm in a collaborative industrial environment, ensuring the maximization of the operator's safety and ergonomics without sacrificing production efficiency requirements. Hence, a multi-objective optimization strategy for trajectory planning in a safe and ergonomic HRC is defined. This approach aims at finding the best trade-off between the total traversal time of the cobot's end-effector trajectory and ergonomics for the human worker, while respecting in the kinematic constraint of the optimization problem the ISO safety requirements through the well-known Speed and Separation Monitoring (SSM) methodology. Guaranteeing an ergonomic HRC means reducing musculoskeletal disorders linked to risky and highly repetitive activities. The three main phases of the proposed technique are described as follows. First, a manikin designed using a dedicated software is employed to evaluate the Rapid Upper Limb Assessment (RULA) ergonomic index in the working area. Next, a second-order cone programming problem is defined to represent a time-optimal safety compliant trajectory planning problem. Finally, the trajectory that ensures the best compromise between these two opposing goals -minimizing the task's traversal time and maintaining a high level of ergonomics for the human worker- is computed by defining and solving a multi-objective control problem. The method is tested on an experimental case study in reference to an assembly task and the obtained results are discussed, showing the effectiveness of the proposed approach.

Safety Compliant, Ergonomic and Time-Optimal Trajectory Planning for Collaborative Robotics / Proia, S; Cavone, G; Scarabaggio, P; Carli, R; Dotoli, M. - In: IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING. - ISSN 1545-5955. - (2023), pp. -12. [10.1109/TASE.2023.3331505]

Safety Compliant, Ergonomic and Time-Optimal Trajectory Planning for Collaborative Robotics

Proia, S;Scarabaggio, P;Carli, R;Dotoli, M
2023-01-01

Abstract

The demand for safe and ergonomic workplaces is rapidly growing in modern industrial scenarios, especially for companies that intensely rely on Human-Robot Collaboration (HRC). This work focuses on optimizing the trajectory of the end-effector of a cobot arm in a collaborative industrial environment, ensuring the maximization of the operator's safety and ergonomics without sacrificing production efficiency requirements. Hence, a multi-objective optimization strategy for trajectory planning in a safe and ergonomic HRC is defined. This approach aims at finding the best trade-off between the total traversal time of the cobot's end-effector trajectory and ergonomics for the human worker, while respecting in the kinematic constraint of the optimization problem the ISO safety requirements through the well-known Speed and Separation Monitoring (SSM) methodology. Guaranteeing an ergonomic HRC means reducing musculoskeletal disorders linked to risky and highly repetitive activities. The three main phases of the proposed technique are described as follows. First, a manikin designed using a dedicated software is employed to evaluate the Rapid Upper Limb Assessment (RULA) ergonomic index in the working area. Next, a second-order cone programming problem is defined to represent a time-optimal safety compliant trajectory planning problem. Finally, the trajectory that ensures the best compromise between these two opposing goals -minimizing the task's traversal time and maintaining a high level of ergonomics for the human worker- is computed by defining and solving a multi-objective control problem. The method is tested on an experimental case study in reference to an assembly task and the obtained results are discussed, showing the effectiveness of the proposed approach.
2023
Safety Compliant, Ergonomic and Time-Optimal Trajectory Planning for Collaborative Robotics / Proia, S; Cavone, G; Scarabaggio, P; Carli, R; Dotoli, M. - In: IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING. - ISSN 1545-5955. - (2023), pp. -12. [10.1109/TASE.2023.3331505]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/264190
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