Project Overview
Critical infrastructure inspection in nuclear power plants, tunnels, and industrial facilities poses significant safety risks to human inspectors while requiring precise, repeatable assessment of complex indoor environments where GPS is unavailable. Our research addresses this challenge by developing an unmanned ground vehicle equipped with advanced semantic SLAM capabilities that create intelligent maps combining precise geometric data from LiDAR and vision sensors with semantic labels from deep learning-based perception systems. The core technical innovation integrates simultaneous localization and mapping with real-time object recognition and scene understanding, enabling the robot to not only navigate autonomously through cluttered, GPS-denied environments but also comprehend and categorize what it observes. Our system features robust multi-sensor fusion, dynamic obstacle avoidance, and persistent mapping capabilities that enable repeatable inspections with precise geo-tagged documentation of findings and environmental changes over time.
This technology transforms hazardous environment inspection by replacing human exposure to radiation, toxic gases, and structural hazards with autonomous robotic systems that deliver superior consistency and safety. The platform enables continuous monitoring of critical infrastructure, automated defect detection, and comprehensive environmental assessment in nuclear facilities, underground tunnels, and industrial plants where human access is dangerous or limited. Applications extend to emergency response scenarios where rapid reconnaissance is essential, routine compliance monitoring, and predictive maintenance programs that rely on consistent data collection. The broader impact includes significant improvements in worker safety, inspection accuracy, operational efficiency, and regulatory compliance. Our team brings expertise in mobile robotics, computer vision, and nuclear engineering, actively seeking partnerships with nuclear industry leaders like Westinghouse, infrastructure inspection companies, and technology firms to deploy this critical autonomous inspection technology in high-stakes environments.