Hantao Jiang
Papers
2
Total Citations
28
H-Index
2
About
Hantao Jiang is a rising researcher in autonomous robotics, specializing in safe motion planning and multi-robot coordination. His work addresses critical challenges in deploying mobile robots in dynamic, real-world environments, particularly where safety and flexibility are paramount. Jiang’s most cited paper, “Safe Reinforcement Learning-Based Motion Planning for Functional Mobile Robots Suffering Uncontrollable Mobile Robots” (2023, 26 citations), tackles the pressing industrial problem of managing out-of-control autonomous mobile robots (AMRs) in warehouses and factories. By integrating reinforcement learning with safety constraints, he provides a novel framework that ensures operational reliability even when some robots malfunction. In his more recent work, “Simultaneous Path and Motion Planning Approaches for Cooperative Cable-Driven Transportation With Mobile Robots” (2025, 2 citations), Jiang explores innovative cable-driven systems that allow robots to collaboratively transport payloads while navigating low obstacles, reducing mutual interference. This comparative study highlights his ability to advance both theoretical planning algorithms and practical robotic applications. With a focus on safety, scalability, and real-world impact, Hantao Jiang’s contributions are shaping the next generation of resilient, cooperative autonomous systems for logistics and manufacturing.
Research Focus
Key Achievements
Top Papers
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- 2