Shiyong Zhang
Papers
7
Total Citations
149
H-Index
5
About
Shiyong Zhang is a robotics researcher whose work centers on autonomous exploration, multi-robot coordination, and intelligent navigation for both aerial and ground platforms. His research addresses some of the most challenging problems in field robotics: enabling robots to efficiently and safely map unknown environments without human intervention. Zhang's most significant contributions include CURE (2023, 48 citations), a hierarchical multi-robot exploration framework leveraging dynamic Voronoi diagrams to coordinate teams of robots through unknown terrain, and a fast aerial exploration system (2022, 44 citations) designed to accelerate traversable path finding for ground robots in search-and-rescue scenarios. His earlier work on air-ground cooperative surveillance (2018, 29 citations) demonstrated practical UAV–UGV teaming for field operations. More recently, he has pushed into uneven terrain navigation through LRAE (2024, 16 citations) and TMPU (2023, 6 citations), tackling safety-critical challenges in rugged environments. His trajectory planning work, including SGS-Planner and HIGHSTAR, reflects a growing focus on high-speed, computationally efficient motion planning in constrained spaces. With over 140 cumulative citations across seven papers, Zhang's research meaningfully advances autonomous robotics for real-world deployment, making him a notable emerging voice in the field.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7HIGHSTAR: High-Speed and Efficient Online Autonomous UAV Exploration2 citations · 2025