  In this study, we introduce an optimization framework aimed at enhancing the
efficiency of motion priority design in scenarios involving automated and
teleoperated robots within an industrial recovery context. The escalating
utilization of industrial robots at manufacturing sites has been instrumental
in mitigating human workload. Nevertheless, the challenge persists in achieving
effective human-robot collaboration/cooperation where human workers and robots
share a workspace for collaborative tasks. In the event of an industrial robot
encountering a failure, it necessitates the suspension of the corresponding
factory cell for safe recovery. Given the limited capacity of pre-programmed
robots to rectify such failures, human intervention becomes imperative,
requiring entry into the robot workspace to address the dropped object while
the robot system is halted. This non-continuous manufacturing process results
in productivity loss. Robotic teleoperation has emerged as a promising
technology enabling human workers to undertake high-risk tasks remotely and
safely. Our study advocates for the incorporation of robotic teleoperation in
the recovery process during manufacturing failure scenarios, which is referred
to as "Cooperative Tele-Recovery". Our proposed approach involves the
formulation of priority rules designed to facilitate collision avoidance
between manufacturing and recovery robots. This, in turn, ensures a continuous
manufacturing process with minimal production loss within a configurable risk
limitation. We present a comprehensive motion priority optimization framework,
encompassing an HRC simulator-based priority optimization and a cooperative
multi-robot controller, to identify optimal parameters for the priority
function. The framework dynamically adjusts the allocation of motion priorities
for manufacturing and recovery robots while adhering to predefined risk
limitations.
