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About

Kun Dai is an emerging robotics and autonomous systems researcher whose work spans 3D perception, simultaneous localization and mapping (SLAM), robot dynamics, and intelligent sensing. His most recognized contribution, Poly-MOT (2023), has garnered over 52 citations and introduced a polyhedral framework for 3D multi-object tracking that addresses a longstanding limitation in the field — the reliance on single similarity metrics and physical models — significantly advancing motion planning and navigation capabilities for mobile robots. His deep visual dynamic SLAM system, DVDS, further demonstrates his commitment to robust real-world perception, while his data-driven work on industrial robot dynamics modeling offers practical tools for identifying complex robot behavior without requiring full kinematic pre-knowledge. Notably, his NL-WCS algorithm extends SINDy-based techniques to handle non-linear friction, a critical refinement for serial robot precision. Dai also bridges robotics with applied sensing, developing a novel inclinometer-integrated structured-light weld vision sensor for challenging welding environments. Across his growing body of work, Dai consistently tackles real-world deployment challenges, positioning himself as a versatile contributor to next-generation intelligent robotic systems.