Papers
4
Total Citations
112
H-Index
4
About
Cong Hu is a leading researcher at the intersection of robotics, artificial intelligence, and intelligent transportation systems. His primary contributions lie in developing novel Deep Reinforcement Learning (DRL) algorithms for autonomous navigation in complex, dynamic environments. Hu’s landmark work, the MK-A3C (Memory and Knowledge-based Asynchronous Advantage Actor-Critic) algorithm, enables non-holonomic robots to perform continuous control and navigate safely among moving obstacles, earning over 70 citations. He further advanced the field with the JPS-IA3C hierarchical framework, which integrates path planning with adaptive motion control for enhanced robustness. In the domain of smart cities, Hu has explored Crowd Sensing Intelligence (CSI) for society-centered Intelligent Transportation Systems (ITS), addressing the integration of Cyber-Physical-Social Systems. His work on applying robotic manipulation to cultural games, such as designing a manipulator for Chinese chess, showcases his versatility. With a growing citation impact and a focus on real-world deployment, Hu’s research is pivotal for the next generation of autonomous systems and human-robot interaction.
Research Focus
Key Achievements
Top Papers
- 1
- 2Crowd Sensing Intelligence for ITS: Participants, Methods, and Stages19 citations · 2023
- 3
- 4Design and Implementation of Chinese Chess Based on Manipulator5 citations · 2019