Energy-Aware Adaptive Communication in ROS2-Based Robotic Applications

In robotic systems, wireless communication is essential for transmitting sensor data, commands, and status information. However, maintaining high communication performance often comes at the cost of increased energy consumption, particularly critical in mobile robots operating on limited power budgets. This thesis presents a modular and flexible adaptive communication framework for robotic applications, based on ROS2 messages, designed to minimise energy consumption while preserving communication reliability. The algorithm uses RSSI (Received Signal Strength Indicator) as a feedback metric to estimate link quality. Based on this estimation, the framework dynamically computes the optimal combination of transmission power and data rate, minimising energy consumption according to the cost associated with each transmission power level, message size, and estimated link quality. In addition, the framework integrates a message prioritisation system that selectively reduces the frequency of lower-priority messages when link quality degrades. This mechanism helps to decrease the effective data rate, thus improving transmission robustness while maintaining essential communication. Designed to be used with ROS2 messages, the framework is suitable for a wide range of robotic applications. Simulations and experimental results demonstrate that the proposed system can reduce communication energy consumption, contributing to more sustainable and intelligent robotic systems.