Papers
196
Total Citations
4,039
H-Index
33
About
Zeng-Guang Hou is a prominent researcher whose work spans robotics, neural networks, and medical robotics — fields where his contributions have reshaped both theoretical foundations and practical applications. His early investigations into adaptive control of nonholonomic mobile robots, combining backstepping techniques with fuzzy logic to handle model uncertainties, garnered over 240 citations and established him as a leading voice in intelligent robot control. This foundational work extended naturally into multi-robot coordination, where his dual neural network and recurrent neural network approaches to redundant robot optimization and optimal formation control have each attracted over 100 citations. Hou's research also bridges human-machine interaction and rehabilitation engineering, exemplified by his highly cited work on sEMG-based continuous joint angle estimation using neural networks — a technique with significant implications for prosthetics and exoskeletons. More recently, he has made notable strides in medical robotics and surgical intelligence, contributing to instrument segmentation in endoscopic procedures and developing a low-cost robotic system for COVID-19 nasopharyngeal swab sampling — a timely innovation addressing real-world healthcare challenges. His survey on neural networks for mobile robot navigation further demonstrates his commitment to synthesizing and advancing the field, cementing his reputation as a versatile and deeply impactful researcher.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5Optimal Formation of Multirobot Systems Based on a Recurrent Neural Network108 citations · 2015
- 6
- 7Neural Networks for Mobile Robot Navigation: A Survey86 citations · 2006
- 8
- 9
- 10