Papers
21
Total Citations
348
H-Index
10
About
Lim Yi is a robotics researcher whose work sits at the intersection of autonomous systems, reconfigurable robotics, and intelligent control, with a particular focus on pavement maintenance and cleaning applications. His most significant contribution lies in pioneering the development of self-reconfigurable mobile robots capable of adapting their physical morphology to navigate pavements of varying widths — a challenge that fixed-form autonomous vehicles have historically struggled to address. His 2021 paper on deep learning-based pavement inspection, which integrates crack detection and garbage recognition into sweeping platforms, has garnered 52 citations, reflecting strong community interest in intelligent infrastructure maintenance. Complementing this, his robust output feedback controller for actuator-saturated reconfigurable robots (47 citations) demonstrates rigorous theoretical grounding alongside practical engineering innovation. Lim Yi has further advanced the field through contributions to complete coverage path planning using grid-based neural networks, heat conduction-inspired optimization methods, switched adaptive control for dynamically changing robot morphologies, and multi-sensor fusion frameworks tailored to reconfigurable platforms. Collectively accumulating over 296 citations, his body of work has meaningfully shaped how researchers approach autonomous cleaning systems, making him a noteworthy figure in service robotics and intelligent control design.
Research Focus
Key Achievements
Top Papers
- 1Deep Learning Based Pavement Inspection Using Self-Reconfigurable Robot52 citations · 2021
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