Sing Yee Ng

Papers

Total Citations

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About

Sing Yee Ng is a researcher in mobile robotics, specializing in bio-inspired and artificial potential field methods for obstacle avoidance. Her work focuses on developing efficient, constraint-aware navigation strategies for nonholonomic wheeled mobile robots, addressing fundamental challenges in autonomous motion planning. Ng’s most-cited paper, "A Bug-Inspired Algorithm for Obstacle Avoidance of a Nonholonomic Wheeled Mobile Robot with Constraints" (2019, 7 citations), introduces a novel approach that mimics insect behavior to navigate complex environments while respecting kinematic and dynamic constraints. Her complementary study, "Obstacle Avoidance Strategy for Wheeled Mobile Robots with a Simplified Artificial Potential Field" (2019, 5 citations), streamlines classical potential field techniques to reduce computational overhead and improve real-time performance. Though her citation counts are modest, Ng’s contributions are notable for their practical focus on real-world robot deployment, bridging theoretical algorithms with hardware limitations. Her work has been recognized in robotics conferences and serves as a foundation for further research in autonomous navigation, particularly for applications in service robots and automated guided vehicles.