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In this study, we introduce an optimization framework aimed at enhancing theefficiency of motion priority design in scenarios involving automated andteleoperated robots within an industrial recovery context. The escalatingutilization of industrial robots at manufacturing sites has been instrumentalin mitigating human workload. Nevertheless, the challenge persists in achievingeffective human-robot collaboration/cooperation where human workers and robotsshare a workspace for collaborative tasks. In the event of an industrial robotencountering a failure, it necessitates the suspension of the correspondingfactory cell for safe recovery. Given the limited capacity of pre-programmedrobots to rectify such failures, human intervention becomes imperative,requiring entry into the robot workspace to address the dropped object whilethe robot system is halted. This non-continuous manufacturing process resultsin productivity loss. Robotic teleoperation has emerged as a promisingtechnology enabling human workers to undertake high-risk tasks remotely andsafely. Our study advocates for the incorporation of robotic teleoperation inthe recovery process during manufacturing failure scenarios, which is referredto as "Cooperative Tele-Recovery". Our proposed approach involves theformulation of priority rules designed to facilitate collision avoidancebetween manufacturing and recovery robots. This, in turn, ensures a continuousmanufacturing process with minimal production loss within a configurable risklimitation. We present a comprehensive motion priority optimization framework,encompassing an HRC simulator-based priority optimization and a cooperativemulti-robot controller, to identify optimal parameters for the priorityfunction. The framework dynamically adjusts the allocation of motion prioritiesfor manufacturing and recovery robots while adhering to predefined risklimitations.

Motion Priority Optimization Framework towards Automated and Teleoperated Robot Cooperation in Industrial Recovery Scenarios