Danny Wee-Kiat Ng

Universiti Tunku Abdul Rahman

Papers

9

Total Citations

98

H-Index

6

About

Danny Wee-Kiat Ng is a robotics researcher whose work spans soft robotics, autonomous navigation, and brain-computer interfaces. His most cited paper introduces an AI-assisted, self-powered smart robotic gripper using Eco-EGaIn nanocomposite for pick-and-place operations, achieving high compliance and muscle-like performance—a contribution that has garnered 31 citations. Ng has also advanced multi-robot path planning with an Enhanced Particle Swarm Optimisation algorithm that integrates Bezier curve smoothing, reducing suboptimal turns in complex trajectories (13 citations). In assistive technology, he developed an indirect control system for autonomous wheelchairs using SSVEP-based brain-computer interfaces, enabling hands-free navigation for patients with motor disabilities (11 citations). His work on human tracking and following via machine vision for mobile service robots (8 citations) and cloud-based ROS implementations for offloading SLAM processes (8 citations) further demonstrates his impact. Ng’s research consistently addresses real-world challenges—from office assistant robots to low-cost 3D-printed differential drive platforms—making his contributions both practical and widely cited across the robotics community.

Research Focus

Key Achievements

6
H-Index
9
Papers
98
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
An AI-Assisted and Self-Powered Smart Robotic Gripper Based on Eco-EGaIn Nanocomposite for Pick-and-Place Operation
31 citations · 2022
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 19
🏛 Institutions: Universiti Tunku Abdul Rahman

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago