# A Task Allocation Approach for Human-Robot Collaboration in Product Defects Inspection Scenarios

arXiv: https://arxiv.org/abs/2009.06423 · HTML: https://mlsanity.com/paper/2009.06423/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Sep 2020.

## Built on by (most cited first, 3 of 3)

- [Task Allocation for Multi-Robot Task and Motion Planning: a case for Object Picking in Cluttered Workspaces](https://mlsanity.com/paper/2110.04089/) (2021)
- [A Task-Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networks](https://mlsanity.com/paper/2104.01549/) (2021)
- [A Two-stage Reinforcement Learning-based Approach for Multi-entity Task Allocation](https://mlsanity.com/paper/2407.00496/) (2024)

## Abstract (arXiv)

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 textscFlexHRC framework presented in citedarvish2018flexible 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 textscFlexHRC 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.