Beixian Lai
Papers
4
Total Citations
51
H-Index
3
About
Beixian Lai is an emerging robotics researcher whose work centers on visual servoing, robot control, and computer vision — particularly the challenge of enabling robots to navigate and manipulate intelligently using camera-based feedback. His research has made significant strides in solving one of the field's most persistent problems: achieving precise 3D robot pose control without relying on pre-calibrated cameras or prior geometric knowledge of the environment. Lai's most cited contribution, "Homography-Based Visual Servoing of Eye-in-Hand Robots With Exact Depth Estimation" (2023, 21 citations), addresses the notoriously difficult problem of time-varying depth estimation in monocular camera systems — a critical bottleneck in real-world robot deployment. His subsequent work on uncalibrated eye-to-hand camera systems (17 citations) advances adaptive visual servoing frameworks by rigorously incorporating parameter convergence analysis, a meaningful theoretical refinement often overlooked by predecessors. Across his growing publication record, Lai consistently pushes the boundaries of uncalibrated and homography-based visual servoing, making robot systems more robust in unstructured environments. With over 50 cumulative citations across just four papers published between 2022 and 2024, his trajectory suggests a researcher poised to become a leading voice in intelligent robot perception and control.
Research Focus
Key Achievements
Top Papers
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