Yuhang Bao
Papers
2
Total Citations
3
H-Index
1
About
Yuhang Bao is a rising researcher in autonomous robotics, specializing in motion planning and multi-robot coordination for unknown environments. His work addresses fundamental challenges in efficient exploration, where robots must navigate cluttered spaces without prior maps. Bao’s most cited paper introduces a novel Bezier curve-based motion planning strategy that optimizes trajectories generated by sampling-based methods, significantly improving path smoothness and efficiency for single-robot exploration. Building on this, his second major contribution proposes a region assignment framework for multi-robot teams, incorporating a frontier enclosure function to prevent redundant exploration and maximize coverage gains. Though early in his career, with his top papers accumulating 2 and 1 citations respectively, Bao’s research demonstrates clear practical impact for field robotics applications like search-and-rescue and planetary exploration. His work bridges the gap between theoretical path optimization and real-world deployment constraints, offering scalable solutions for coordinated autonomous systems. As an emerging voice in the robotics community, Bao’s focus on efficient, cooperative exploration positions him to make lasting contributions to autonomous navigation in GPS-denied or hazardous environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2