Energy-Aware Optimization of Multi-Robot Systems with Task Allocation and Partial Recharge Scheduling

This paper presents a task allocation and scheduling model for multi-robot systems operating under energy constraints. The proposed model integrates key factors such as energy consumption, battery charging management, and task execution efficiency. To address this problem, we employ both an exact solver-based method and a bio-inspired algorithm, enabling a comparative analysis of their performance in terms of solution quality and computational efficiency. Experimental results highlight the trade-offs between execution time, energy consumption, and task scheduling efficiency. These insights contribute to optimizing task scheduling in multi-robot systems while minimizing energy expenditure. The proposed framework offers a promising solution for balancing energy constraints and task efficiency in collaborative robotic missions.

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Publication Details

Published
2025-07-15
DOI
https://doi.org/10.1109/codit66093.2025.11321551
Primary Topic
Teleoperation and Haptic Systems
Type
article
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article

Energy-Aware Optimization of Multi-Robot Systems with Task Allocation and Partial Recharge Scheduling

Ouahib Guenounou, Karim Beddiar, Ahmed Nait Chabane, Germain Junior Avossevou
Teleoperation and Haptic Systems
article

Energy-Aware Optimization of Multi-Robot Systems with Task Allocation and Partial Recharge Scheduling

Ouahib Guenounou, Karim Beddiar, Ahmed Nait Chabane, Germain Junior Avossevou
article en

Abstract

This paper presents a task allocation and scheduling model for multi-robot systems operating under energy constraints. The proposed model integrates key factors such as energy consumption, battery charging management, and task execution efficiency. To address this problem, we employ both an exact solver-based method and a bio-inspired algorithm, enabling a comparative analysis of their performance in terms of solution quality and computational efficiency. Experimental results highlight the trade-offs between execution time, energy consumption, and task scheduling efficiency. These insights contribute to optimizing task scheduling in multi-robot systems while minimizing energy expenditure. The proposed framework offers a promising solution for balancing energy constraints and task efficiency in collaborative robotic missions.

Centre d'Etudes Superieures Industrielles (FR)
Affordable and clean energy
Openalex Percentile: Top 42%
Teleoperation and Haptic Systems
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