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About

Gustaf Hendeby is a leading researcher in sensor fusion, target tracking, and autonomous systems, with a focus on enabling robust perception in dynamic and adversarial environments. His work bridges theoretical estimation methods with practical applications in robotics and intelligent transportation. Among his notable contributions, Hendeby developed a framework for network-constrained tracking of cyclists and pedestrians, leveraging connected mobile sensor platforms such as self-driving vehicles and drones to enhance situational awareness (9 citations). He also pioneered sound source localization using wearable microphone arrays fused with inertial sensors, enabling directional audio amplification and robust tracking despite orientation changes (7 citations). To address long-term autonomy, Hendeby proposed a feature-based multi-hypothesis map representation for localization in non-static environments, drawing on target tracking principles to handle environmental uncertainty (5 citations). Additionally, his work on informative path planning under adversarial observers tackles the challenge of maximizing data collection while minimizing exposure to hostile agents (4 citations). Through these innovations, Hendeby has significantly advanced the reliability and intelligence of autonomous systems, making his research essential reading for students and engineers working on sensor fusion, mobile robotics, and real-world perception challenges.