Papers
4
Total Citations
51
H-Index
4
About
Zhirui Sun is an emerging robotics researcher whose work centers on autonomous mobile robot navigation, motion planning, and intelligent systems for real-world service environments. His research has made notable contributions to the challenge of deploying robots in dynamic, crowded public spaces — particularly airports and shopping malls — where reliability, safety, and efficiency are paramount. Sun's most impactful work includes the development of Multi-Risk-RRT, an efficient motion planning algorithm tailored for autonomous luggage trolley collection at airports, which has garnered 23 citations since its 2024 publication. Building on this, his NAMR-RRT framework introduces neural adaptive planning capabilities for mobile robots navigating unpredictable environments, reflecting a growing integration of machine learning into classical robotics planning. His contributions extend to full system design, having engineered an autonomous multi-trolley collection system addressing nonholonomic robot control and real-world implementation challenges. Sun has further advanced the field through systematic evaluations of indoor localization methods, providing valuable benchmarks for the broader robotics community. With a cumulative citation count exceeding 50 across recent publications alone, Sun's focused yet rapidly growing body of work positions him as a promising voice in applied autonomous robotics and intelligent navigation research.
Research Focus
Key Achievements
Top Papers
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