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About

Kevin B. de Carvalho is a robotics researcher whose work bridges multi-robot systems, autonomous navigation, and socially assistive technology. His most influential contribution, "Gestures-teleoperation of a heterogeneous multi-robot system" (22 citations), pioneers intuitive human-robot interaction by enabling gesture-based control of diverse robot teams—a critical step toward seamless collaboration in field operations. In autonomous navigation, he developed a hybrid path-planning strategy for mobile robots with limited sensors (12 citations), offering a computationally efficient solution that requires no prior environmental knowledge, making it ideal for real-world deployment. His 3D Q-Learning algorithm for offline UAV path planning (7 citations) introduces priority-shifting rewards to optimize drone trajectories in complex, three-dimensional spaces. More recently, his overview of machine learning for UAV navigation (2024, 13 citations) synthesizes emerging trends in aerial autonomy. Carvalho also explores the intersection of robotics and education, applying action recognition to social assistive robotics (13 citations) for learning environments. His work consistently addresses practical constraints—limited sensors, heterogeneous platforms, and real-time interaction—making his algorithms directly applicable to defense, exploration, and assistive technologies.