Maximum Sustainable Yield Problem for Robot Foraging and Construction System
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 2725-2730.
Abstract
We introduce the Maximum Sustainable Yield problem for a multi-robot foraging and construction system, inspired by the relationship between the natural resource growth and harvesting behaviors in an ecosystem. The resources spawn according to the logistic model and are vulnerable to overharvesting. The robots must maintain sustainability while maximizing productivity. The foraging robots harvest different types of resources, which enable a construction robot to build new foraging robots. We design algorithms to perform robot construction, assignment, and scheduling. We propose an adaptive algorithm to overcome the problem that resource growth model is often unknown. We demonstrate that our algorithms are robust to noises in the actuation and the environment. The case where the observation noise could harm sustainability is discussed.
@inproceedings{ijcai2016p387,
title = {Maximum Sustainable Yield Problem for Robot Foraging and Construction System},
author = {Zhang, Ruohan and Song, Zhao},
booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-16}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Subbarao Kambhampati},
pages = {2725--2730},
year = {2016},
month = {7},
url = {https://ijcai.org/proceedings/2016/387},
}
TY - CPAPER TI - Maximum Sustainable Yield Problem for Robot Foraging and Construction System AU - Zhang, Ruohan AU - Song, Zhao T2 - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2016 SP - 2725 EP - 2730 UR - https://ijcai.org/proceedings/2016/387 ER -Copied
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