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.