Semantic knowledge driven utility calculation towards efficient multi-robot task allocation

Chayan Sarkar, Sounak Dey, and Marichi Agarwal, "Semantic knowledge driven utility calculation towards efficient multi-robot task allocation", 14th IEEE International Conference on Automation Science and Engineering (CASE), Munich, Germany, IEEE, 2018.

Abstract

With the advent of Industry 4.0 era, employing a team of robots within a factory floor or a warehouse is pretty prevalent today as robots can perform a known task with higher accuracy and efficiency if its capability permits. Efficiency and throughput of such a setup depend on careful task assignment and scheduling, which further depend on utility calculation. Though there exists a number of techniques to perform efficient task allocation, they assume the utility values are available and static. They neither consider all the relevant parameters nor the dynamic changes that may occur during task execution. Moreover, methods of automating such dynamic utility calculation (both at the start and at runtime) based on knowledge and semantics are not present and this is a hindrance to building a fully automated robotic workforce. In this article, we explore an avenue of semantic-based dynamic utility calculation and showcase its application for a use-case.

BibTex entry

@inproceedings{sarkar2018utility,
    title={Semantic knowledge driven utility calculation towards efficient multi-robot task allocation},
    author={Sarkar, Chayan and Dey, Sounak and Agarwal, Marichi},
    booktitle={14th IEEE International Conference on Automation Science and Engineering (CASE)},
    year={2018},
    organization={IEEE}
}