A Task Allocation Approach for Human-Robot Collaboration in Product Defects Inspection Scenarios
This work addresses task allocation challenges in industrial inspection scenarios involving humans and robots, but it is incremental as it builds upon an existing framework.
The paper tackles the problem of task allocation in human-robot collaboration for product defects inspection by extending the FlexHRC framework to enable a human operator to interact with multiple heterogeneous robots simultaneously, resulting in a dynamic collaboration process demonstrated in a specific use case.
The presence and coexistence of human operators and collaborative robots in shop-floor environments raises the need for assigning tasks to either operators or robots, or both. Depending on task characteristics, operator capabilities and the involved robot functionalities, it is of the utmost importance to design strategies allowing for the concurrent and/or sequential allocation of tasks related to object manipulation and assembly. In this paper, we extend the \textsc{FlexHRC} framework presented in \cite{darvish2018flexible} to allow a human operator to interact with multiple, heterogeneous robots at the same time in order to jointly carry out a given task. The extended \textsc{FlexHRC} framework leverages a concurrent and sequential task representation framework to allocate tasks to either operators or robots as part of a dynamic collaboration process. In particular, we focus on a use case related to the inspection of product defects, which involves a human operator, a dual-arm Baxter manipulator from Rethink Robotics and a Kuka youBot mobile manipulator.