UConn advances autonomous drone research for maritime and infrastructure missions
UConn engineers are pushing drone research toward autonomous swarms for maritime, industrial and infrastructure missions. The work brings together artificial intelligence, edge computing, network integration and systems engineering to help unmanned aircraft sense their surroundings, coordinate with one another and make decisions in fast-changing environments. The effort is led by George Bollas, Jonathan Shihao Ji and Shalabh Gupta through UConn’s College of Engineering and its advanced systems engineering research programs.
One major initiative is a proposed collaboration among UConn, the United States Coast Guard Academy and the United States Coast Guard Research and Development Center. The partnership is designed to pilot a research and development program for AI-enabled autonomous and swarm-based maritime drone operations, involving engineering staff and students from UConn and the academy. The planned work is aimed at Coast Guard missions including search and rescue, maritime domain awareness, environmental monitoring, pollution response, intelligence gathering, port security and event security.
A second initiative links UConn with RTX, Sikorsky and the Connecticut Center for Advanced Technology to improve multi-drone systems. The goal is to allow drones to learn from each other and from their operating environment, reducing reliance on direct human control and improving performance across a fleet. Using AI algorithms, edge computing, communications networks and system integration, the project is intended to support applications including traffic management in major cities, large-scale facility inspection, aerial photography, precision agriculture and search and rescue.
The core technical challenge is autonomy. Bollas contributes expertise in complex systems and energy processes, with a focus on how aerial platforms can connect with industrial operations, environmental sensing and energy-efficiency needs. Ji, who directs the Intelligent Systems Lab, works on the integration of AI into robotic platforms including drones, robotic dogs and robotic arms; his work is central to multi-drone sensing, where aircraft may need to collaborate to detect ground objects even when weather, terrain or other objects limit visibility.
Gupta, director of UConn’s robotics engineering program and the Laboratory of Intelligent Networked Systems, is focused on perception, diagnostics, motion planning and autonomy in real operating conditions. His research examines how multi-drone teams can detect anomalies, build situational awareness and plan time-risk optimal flight paths in constrained environments, while remaining resilient if one machine fails or loses battery power. A separate project being finalized for award by the Connecticut Department of Transportation’s Research Unit would apply drones, LiDAR, sonar, AI-based defect detection and GPS-denied navigation to culvert inspections in confined or hazardous areas; if validated in field trials, the work could make emergency response, infrastructure inspection and asset management safer, faster and more reliable.