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About

Kevin Carey is a robotics researcher whose work centers on the foundational theory and practical autonomy of multi-agent systems and mobile robots. His most influential contribution is a definitive 2019 paper, “What is A Robot Swarm: A Definition for Swarming Robotics,” which has garnered 49 citations by providing a clear, operational taxonomy for the field—a critical step in bridging the gap between theoretical swarm intelligence and real-world deployment. Beyond swarming, Carey tackles the core challenges of autonomous navigation and resource-constrained planning. He has explored the use of deep reinforcement learning (a Deep Q-Network with one-hot image encoding) for autonomous driving, and has advanced the concept of metareasoning to help robots optimally allocate their limited onboard computational power during complex missions. His applied work also includes a rigorous performance comparison of inertial measurement units fused with odometry for GPS-denied navigation, offering practical guidance for vehicle designers. By combining conceptual clarity with hardware-aware solutions, Carey’s research directly supports the development of more capable, efficient, and truly autonomous robots.