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

TL;DR

This paper presents a motion priority optimization framework that enables safe and efficient collaboration between automated and teleoperated robots during industrial recovery, minimizing production loss and ensuring safety.

Contribution

It introduces a novel optimization framework for dynamic motion priority allocation in human-robot collaboration during recovery scenarios, incorporating collision avoidance and risk management.

Findings

Framework effectively reduces production loss during robot recovery.

Dynamic priority adjustment improves safety and efficiency.

Simulation results validate the approach's effectiveness.

Abstract

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.