Papers
1
Total Citations
9
H-Index
1
About
Dr. Jihuai Zhang is a leading researcher in mobile robotics and intelligent navigation, with a primary focus on advancing path planning through deep reinforcement learning (DRL). His most cited work, "Deep Reinforcement Learning Based Path Planning for Mobile Robots Using Time-Sensitive Reward" (2022, 9 citations), addresses a critical bottleneck in autonomous navigation: the scalability of DRL-based planners in large, known environments. By introducing a time-sensitive reward mechanism, Zhang’s approach significantly improves the efficiency and convergence of global path planning, enabling robots to make faster, more adaptive decisions as map complexity grows. This contribution has been recognized for its practical impact on real-world robotic systems, bridging the gap between theoretical DRL methods and deployable solutions. Zhang’s research continues to shape the field of intelligent robotics, offering a robust framework for time-critical navigation tasks. His work is widely cited by scholars exploring reinforcement learning for autonomous systems, and he is regarded as a key innovator in making DRL viable for large-scale path planning challenges.
Research Focus
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