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Multi-robot Task Allocation System: Fuzzy Auction-Based and Adaptive Multi-threshold Approaches

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Abstract

Auction-based and threshold-based are the prevalent approaches for multi-robot distributed task allocation problem. We study the performance of these two approaches under a multi-objective dynamic task allocation scenario. The fuzzy inference system (FIS) is used in the auction-based approach to convert the objectives into a representative bid value. Experiments reveal that FIS auction-based outperforms the adaptive threshold-based approach in terms of load balancing. In contrast, the adaptive threshold-based approach produces better results in terms of traveled distance. Moreover, both approaches can achieve the same quality satisfaction objective.

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Acknowledgements

The authors would like to acknowledge the support provided by the National Plan for Science, Technology, and Innovation (MAARIFAH)-King Abdulaziz City for Science and Technology through the Science and Technology Unit at King Fahd University of Petroleum and Minerals (KFUPM), the Kingdom of Saudi Arabia, Award project no. 11-ELE2147-4.

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  1. Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    Mohammed Alshaboti & Uthman Baroudi

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  1. Mohammed Alshaboti
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  2. Uthman Baroudi
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Correspondence to Uthman Baroudi.

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Mohammed Alshaboti declares that he has no conflict of interest. Uthman Baroudi declares that he has no conflict of interest.

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Alshaboti, M., Baroudi, U. Multi-robot Task Allocation System: Fuzzy Auction-Based and Adaptive Multi-threshold Approaches. SN COMPUT. SCI. 2, 87 (2021). https://doi.org/10.1007/s42979-021-00479-x

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