Mobile robots are being used ever more to carry out tasks in outdoor environments, where the main limitation to their autonomous operation is mainly the capacity of the battery system. The aim of this thesis was to experimentally analyze the impact of driving speed and terrain slope on the battery drain of the Leo Rover mobile robot and to develop an empirical model for predicting energy consumption. We conducted measurements on two robotic platforms in both laboratory and field conditions, at different driving speeds, slopes, and turns. We processed the data collected from the ROS2 system in Python and then analyzed it using multiple linear regression. Based on the experimental results, we determined models to predict battery voltage drop per minute and per distance traveled. The results showed that driving speed and terrain slope are important factors in battery drain, with the slope having a more noticeable impact on energy usage over time, while the effect of speed also depends on how the consumption is measured. The models developed provide a useful basis for estimating the energy use of mobile robots and planning their operation and battery charging strategies.
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