Papers
10
Total Citations
177
H-Index
5
About
Xiuqing Wang is a leading researcher in autonomous mobile robotics, with a career-long focus on bio-inspired control systems and intelligent navigation. Her pioneering work integrates spiking neural networks (SNNs) into mobile robot controllers, most notably in her highly cited 2007 paper on a behavior controller for mobile robots (74 citations) and her 2014 modular navigation controller (48 citations). Wang has made significant contributions to wall-following and target-reaching strategies using spiking neurons, and has advanced scene classification methods—such as corridor-scene classifiers based on probabilistic spiking neuron models—that enable robots to recognize and navigate complex environments using multi-sonar sensor fusion. More recently, she has expanded into deep reinforcement learning, proposing path planning algorithms like TPR-DDPG (2021, 14 citations) and applying deep convolutional neural networks to classify robot execution failures (2019). Her work bridges classical neural computation with modern AI, demonstrating how SNNs can provide efficient, biologically plausible solutions for real-time robot control. With over 170 total citations across her most influential papers, Wang’s research continues to inspire new generations of roboticists exploring the intersection of neuroscience and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1A behavior controller based on spiking neural networks for mobile robots74 citations · 2007
- 2Mobile robots׳ modular navigation controller using spiking neural networks48 citations · 2014
- 3The Wall-Following Controller for the Mobile Robot Using Spiking Neurons17 citations · 2009
- 4Path Planning for Mobile Robots Based on TPR-DDPG14 citations · 2021
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- 8Mobile robot path planning based on Q-learning algorithm3 citations · 2019
- 9
- 10Scene Analysis for Mobile Robot Based on Multi-Sonar-Ranger Data3 citations · 2006