Demand-Aware Multi-Robot Task Scheduling with Mixed Reality Simulation

Sandula, AK and Khokhar, A and Ghose, D and Biswas, P (2023) Demand-Aware Multi-Robot Task Scheduling with Mixed Reality Simulation. In: UNSPECIFIED, pp. 1606-1611.

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Abstract

This paper addresses the problem of multi-robot task scheduling by estimating the demand for the tasks in a real-world scenario. Scheduling tasks for multiple robots becomes complex when a human is involved in allocating limited resources. We propose a stochastic multi-agent multi-armed bandit based task scheduler which prioritizes the tasks based on the estimated demand for the tasks. To gain insight into the varying priorities of a human task allocator in a multi-armed bandit scenario, we conducted a user study in a Mixed Reality environment which can be used to customize the resource allocation process. We observe that the users consistently made sub-optimal choices due to their preference to minimize other parameters (such as cumulative distance travelled) of the real world scenario rather than strictly adhering to the optimal strategy. Our proposed method uses the Thompson sampling bandit algorithm with ϵ-greedy approach to solve the multi-agent multi-armed bandit problem. The approach outperformed other methods such as first-come-first-serve, rate monotonic scheduling, and heuristic-based Min-interference approaches in terms of the demand aware performance index. © 2023 IEEE.

Item Type:	Conference Paper
Publication:	IEEE International Workshop on Robot and Human Communication, RO-MAN
Publisher:	IEEE Computer Society
Additional Information:	The copyright for this article belongs to IEEE Computer Society.
Department/Centre:	Division of Interdisciplinary Sciences > Robert Bosch Centre for Cyber Physical Systems
Date Deposited:	15 May 2024 11:53
Last Modified:	15 May 2024 11:53
URI:	https://eprints.iisc.ac.in/id/eprint/84506

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