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About

Dr. Tan is a pioneering researcher in swarm robotics and mobile robot control, whose work has fundamentally advanced autonomous navigation and multi-robot coordination. His most influential contribution is the development of an Ant Colony System (ACS) algorithm for real-time global path planning, published in 2007 and cited 60 times. This innovative three-step method—using MAKLINK graph theory for spatial modeling, Dijkstra’s algorithm for initial collision-free paths, and ACS optimization for global optimality—demonstrated superior convergence speed, solution stability, and computational efficiency over genetic algorithm-based approaches. Dr. Tan also made significant strides in formation control, introducing a unified algorithm that enables follower robots to maintain relative positioning with a leader while actively avoiding obstacles, requiring only relative motion states rather than absolute leader positions. This work, cited 11 times, was validated through experiments with nonholonomic robots and computer vision systems. Additionally, his 2013 review on swarm robotics (10 citations) has guided subsequent research in collective behavior. Dr. Tan’s contributions have established foundational methods for real-time, adaptive robot navigation and cooperative control, directly impacting applications in industrial automation and autonomous systems.