RUGGED

RUGGED addresses a critical gap in autonomous ground robotics: reliable operation in harsh, unstructured outdoor environments such as agriculture, forestry, and wildfire scenarios. While perception, localization, and navigation have advanced rapidly in controlled settings, little is known about how robotic systems and sensors degrade under dust, smoke, debris, extreme vibrations, and high temperatures. RUGGED tackles this problem head-on by jointly addressing hardware robustness and software resilience.The project follows a strongly experimental, multidisciplinary approach combining electrical and mechanical engineering with robotics and AI. It begins with a systematic assessment of how environmental stressors affect sensors, electronics, and perception pipelines, using both laboratory tests and real-world field trials with forestry machinery. Based on this evidence, RUGGED develops mitigation strategies at two levels: hardware solutions, such as optimized sensor placement, vibration damping, and thermal management; and software solutions, including robust multisensory perception, localization, and mapping.On the software side, the project advances real-time sensor fusion using complementary modalities (LiDAR, RADAR, depth, multispectral and thermal cameras), metric-semantic mapping, traversability analysis, and multimodal localization. These methods are developed and validated using noise-rich virtual environments and real datasets, within a ROS-based framework. The project concludes with large-scale field validation in progressively challenging scenarios and the release of open multisensory datasets. RUGGED ultimately delivers practical guidelines, validated technologies, and data resources to enable dependable semi-autonomous robots in extreme outdoor operations.