Lye Zhenjun

Universiti Tunku Abdul Rahman

Papers

2

Total Citations

10

H-Index

2

About

Lye Zhenjun has made significant contributions to the field of autonomous robotics, with a primary focus on indoor robot navigation and real-time localization. His research centers on integrating advanced computer vision techniques with practical robotic platforms, particularly through the use of Monte Carlo Localization and ORB (Oriented FAST and rotated BRIEF) feature detection. In his most cited work (2014, 7 citations), Zhenjun introduced a pioneering framework that enables a Lego Mindstorms NXT robot to autonomously explore and navigate known indoor environments, leveraging an Android device for object recognition and decision-making. This work demonstrated a cost-effective, scalable approach to real-time navigation. His subsequent study (2014, 3 citations) further validated the feasibility of ORB—a binary, rotation-invariant, and noise-resistant algorithm—for indoor feature recognition, highlighting its robustness over traditional methods. Though early in his career, Zhenjun’s integration of accessible hardware with sophisticated algorithms has laid groundwork for affordable autonomous systems, inspiring further research in embedded robotics and computer vision applications.

Research Focus

Key Achievements

2
H-Index
2
Papers
10
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
A framework for real time indoor robot navigation using Monte Carlo Localization and ORB feature detection
7 citations · 2014
📈 Most Prolific Year: 2014 (2 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Universiti Tunku Abdul Rahman

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago