Papers
8
Total Citations
144
H-Index
7
About
Patrick Goh is a robotics and intelligent systems researcher whose work bridges autonomous navigation, human-robot interaction, and sensor fusion. His research focuses on enabling robots to perceive and respond to their environments with greater precision and safety. Goh’s most cited paper, “Close Proximity Time-to-collision Prediction for Autonomous Robot Navigation” (36 citations), introduces an exponential Gaussian process regression approach that fuses X-band Doppler radar with infrared sensors for obstacle speed and direction detection. He has also made significant contributions to bionic control systems, developing a flex sensor compensator via Hammerstein–Wiener modeling for improved dynamic goniometry in bionic hands (25 citations). His work on RFID-based navigation (30 citations) and reactive brain-computer interfaces using visual stimuli (22 citations) demonstrates his versatility across sensing modalities. More recently, Goh has explored material classification through embedded RF antenna arrays and machine learning, as well as accelerating real-time robotic systems with large language models. His research consistently addresses practical challenges in autonomous systems, from self-balancing robots to robust hand gesture recognition using YOLO architectures, making him a notable figure in applied robotics and intelligent control.
Research Focus
Key Achievements
Top Papers
- 1
- 2Autonomous Mobile Robot Navigation via RFID Signal Strength Sensing30 citations · 2020
- 3
- 4
- 5
- 6
- 7
- 8