Hui Pang
Papers
5
Total Citations
162
H-Index
5
About
Hui Pang is a leading researcher in autonomous mobile robotics, specializing in intelligent path planning, adaptive control, and deep reinforcement learning for unknown and complex environments. Their work addresses critical challenges such as environmental dependence, slow convergence, and disturbance rejection in robot navigation. Pang’s most impactful contribution, "Path Planning of Autonomous Mobile Robot in Comprehensive Unknown Environment Using Deep Reinforcement Learning," has garnered 94 citations, introducing a novel approach that significantly reduces inference time and enhances anti-disturbance ability. They have also advanced sliding mode control with an integrated learning-based RBFNN for two-wheel mobile robots (37 citations) and developed a RISE-based asymptotic prescribed performance trajectory tracking controller. Their improved Q-Learning algorithm, optimized with flower pollination, solves obstacle avoidance and convergence issues for unmanned ground robots (11 citations). With a total of over 160 citations across their top works, Pang’s research is pivotal for real-world autonomous navigation, offering robust, adaptive solutions that push the boundaries of mobile robot autonomy in unstructured settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5