Productive Multitasking for Industrial Robots
Abstract
The application of robotic solutions to small-batch production is challenging: economical constraints tend to dramatically limit the time for setting up new batches. Organizing robot tasks into modular software components, called skills, and allowing the assignment of multiple concurrent tasks to a single robot is potentially game-changing. However, due to cycle time constraints, it may be necessary for a skill to take over without waiting on another to terminate, and the available literature lacks a systematic approach in this case. In the present article, we fill the gap by (a) establishing the specifications of skills that can be sequenced with partial executions, (b) proposing an implementation based on the combination of finite-state machines and behavior trees, and (c) demonstrating the benefits of such skills through extensive trials in the environment of ARIAC (Agile Robotics for Industrial Automation Competition).
Keywords
Cite
@article{arxiv.2108.11471,
title = {Productive Multitasking for Industrial Robots},
author = {D. Wuthier and F. Rovida and M. Fumagalli and V. Krüger},
journal= {arXiv preprint arXiv:2108.11471},
year = {2021}
}
Comments
To appear in the proceedings of the 2021 IEEE international conference on robotics and automation (ICRA). This research was supported by the European Commission's Horizon 2020 Programme under grant agreement no.~723658 (ScalABLE 4.0) and by the Wallenberg Autonomous Systems Program (WASP) of Sweden