Papers
88
Total Citations
1,532
H-Index
22
About
Tin Lun Lam is a robotics researcher whose work spans climbing robots, modular self-reconfigurable systems, multi-robot coordination, and soft robotics. He is perhaps best known for pioneering the Treebot platform — a biologically inspired, continuum-structured climbing robot capable of navigating irregular tree environments and transitioning from trunk to branch, a capability that surpassed contemporary state-of-the-art systems. His two papers on Treebot's design and autonomous climbing strategy have collectively garnered over 160 citations, demonstrating lasting influence in field robotics. Lam has also made significant contributions to modular robotics, developing FreeBOT and FreeSN — innovative self-reconfigurable systems using magnetic, genderless connections that enable freeform assembly, earning over 140 combined citations. His research extends into multi-robot intelligence, including a semantic histogram-based approach to global localization in large-scale SLAM environments (78 citations) and a turn-minimizing coverage path planning algorithm. More recently, his snail-inspired robotic swarm addresses the critical challenge of outdoor adaptability in unstructured environments. With a portfolio accumulating over 660 citations across diverse robotics subfields, Lam represents a broad and impactful voice in intelligent, adaptive robotic systems research.
Research Focus
Key Achievements
Top Papers
- 1A flexible tree climbing robot: Treebot - design and implementation108 citations · 2011
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- 4Deep Depth Completion from Extremely Sparse Data: A Survey70 citations · 2022
- 5Climbing Strategy for a Flexible Tree Climbing Robot—Treebot60 citations · 2011
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