Optimizing Energy Efficiency in Mobile Robots: A Battery-Aware Dynamic Path Planning Approach

Energy-efficient path planning is a critical research area for mobile robots, particularly batteries. The primary objective of this paper is to identify the paths that require the least energy consumption, thereby minimizing battery usage. In this study, we demonstrate that energy consumption along a given path is influenced by the battery’s state of charge (SOC), leading to significant variations in energy consumption based on different battery levels. We propose a battery-aware path planning algorithm that dynamically adjusts path selection based on the estimated battery SOC in real time to address this relationship. Our algorithm continuously evaluates and adapts paths to optimize energy efficiency during robot operation. Experimental results validate the effectiveness of our approach, achieving up to a 22.87% reduction in energy consumption compared to the baseline.

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Publication Details

Published
2025-05-09
DOI
https://doi.org/10.1109/iccre65455.2025.11093555
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Optimizing Energy Efficiency in Mobile Robots: A Battery-Aware Dynamic Path Planning Approach

Mohammad-Hashem Haghbayan, Eero Immonen, Juha Plosila, Mohsen Heydarzadeh et al.
Robotic Path Planning Algorithms
article

Optimizing Energy Efficiency in Mobile Robots: A Battery-Aware Dynamic Path Planning Approach

Mohammad-Hashem Haghbayan, Eero Immonen, Juha Plosila, Mohsen Heydarzadeh, Wu Chen
article en

Abstract

Energy-efficient path planning is a critical research area for mobile robots, particularly batteries. The primary objective of this paper is to identify the paths that require the least energy consumption, thereby minimizing battery usage. In this study, we demonstrate that energy consumption along a given path is influenced by the battery’s state of charge (SOC), leading to significant variations in energy consumption based on different battery levels. We propose a battery-aware path planning algorithm that dynamically adjusts path selection based on the estimated battery SOC in real time to address this relationship. Our algorithm continuously evaluates and adapts paths to optimize energy efficiency during robot operation. Experimental results validate the effectiveness of our approach, achieving up to a 22.87% reduction in energy consumption compared to the baseline.

University of Turku (FI), Turku University of Applied Sciences (FI)
Academy of Finland
Affordable and clean energy
Openalex Percentile: Top 83%
Robotic Path Planning Algorithms
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