Bing-Gang Jhong

National Taiwan Normal University

Papers

3

Total Citations

15

H-Index

2

About

Bing-Gang Jhong is a robotics researcher whose work focuses on intelligent navigation, motion planning, and adaptive control for mobile robots and robotic manipulators. His most impactful contribution is a real-time path planning algorithm for wheeled mobile robots operating in dynamic environments, which leverages the Markov decision process (MDP) to enable optimal decision-making under uncertainty. This work has garnered 8 citations and represents a significant step toward autonomous navigation in unpredictable settings. Jhong has also advanced motion planning through an enhanced navigation algorithm integrating bidirectional rapidly-exploring random trees (RRT) with path pruning and smoothing, combined with an adaptive controller for two-wheeled robots. Earlier in his career, he developed a variable step-size adaptive sliding mode controller with an exponential reaching law for robot arm trajectory tracking, addressing uncertainties and external disturbances. Though his citation counts are still growing, Jhong’s work demonstrates a clear trajectory from foundational control theory to practical, real-time robotic systems, making him a promising voice in the field of autonomous mobile robotics.

Research Focus

Key Achievements

2
H-Index
3
Papers
15
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
A Real-Time Path Planning Algorithm Based on the Markov Decision Process in a Dynamic Environment for Wheeled Mobile Robots
8 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: National Taiwan Normal University

Top Papers

  1. 1
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  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago