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Towards a Prolonged Productivity in Industry 4.0: A Framework for Fatigue Minimisation in Robot-Robot Co-Manipulation

Edoardo Lamon, Luka Peternel, Arash Ajoudani

Year
2018
Citations
11

Abstract

Industry 4.0 envisions the integration of flexible and quickly reconfigurable robotic systems in assembly lines. This has led to the development of light-weight and adaptive collaborative robots with limited power and payload constraints. Hence, repetitive tasks or those that demand high forces may exceed such limits, resulting in robot damage and lost productivity. To address this problem, we propose a novel framework to prolong the lifetime of collaborative robots while guaranteeing the desired level of productivity. To address this, we propose a method that minimises a function of robot fatigue, an index able to model the robot motor usage at the joint level. This index features the desired external force, task duration, hardware parameters, and fatigue history. Moreover, future tasks are considered through fatigue thresholds imposed on specific joints, computed according to the robot safety requirements. We proved the effectiveness of the approach by comparing its results in terms of fatigue and torque with the well-known minimum effort approach. The results showed that our method ensures that the fatigue thresholds are not exceeded.

Keywords

RobotPayload (computing)TorqueComputer scienceRobot controlTask (project management)Control engineeringProductivitySimulationEngineering

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