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About

Dalong Tan is a robotics researcher whose work spans mobile robot control, humanoid robotics, and multi-robot coordination. His research has made notable contributions to formation control, kinematics modeling, and autonomous navigation, establishing him as a productive voice in intelligent robotic systems during the mid-2000s. Tan's most influential work focuses on multi-robot formation control, with his leader-follower formation framework (46 citations) and active obstacle avoidance for robot formations (37 citations) offering robust solutions grounded in second-order kinematics. These contributions addressed real-world challenges of coordinating mobile robot teams in dynamic environments. His parallel investigations into collision avoidance and trajectory generation using mixed-integer linear programming further broadened the scope of his motion planning research. On the hardware side, Tan contributed meaningfully to humanoid robotics, developing a highly flexible 7-DOF anthropomorphic robotic arm and advancing ZMP-based dynamic stability analysis for wheel-based humanoid systems. His kinematics work on six-wheeled mobile robots navigating uneven terrain, including his innovative "Wheel-Center Modeling" method, demonstrates a consistent commitment to bridging theoretical modeling with practical locomotion challenges. Collectively, his publications have accumulated over 180 citations, reflecting a solid and lasting impact on foundational robotics research.