Although the Robot Operating System (ROS) has become the de facto standard for robotic software development, there are still limited solutions available for Prognostics and Health Management (PHM) within the ROS ecosystem. Predicting equipment health, estimating Remaining Useful Life (RUL), forecasting potential failures before they occur, and supporting autonomous decision-making are essential capabilities for next-generation autonomous robots and industrial automation systems.

This project proposes the development of a comprehensive ROS-based Prognostics and Health Management (PHM) framework using model-based methodologies. The platform is designed to monitor and manage robot health, estimate Remaining Useful Life (RUL), calculate the Probability of Task Completion (PoTC), and support predictive maintenance and mission planning for autonomous robotic systems.

The framework enables users to configure system models by defining robot architecture, hazard rates, and other operational parameters, while integrating real-time sensor data such as temperature, humidity, pressure, and payload conditions. In addition, the project develops a dedicated PHM package for mobile robots, providing an extensible solution for health monitoring, predictive diagnostics, and lifecycle management within the ROS ecosystem.

The project has two primary objectives: the development of a general-purpose Prognostics and Health Management framework for ROS, and the creation of a specialized PHM package for Autonomous Mobile Robots (AMRs) and mobile robotic platforms.