Papers
10
Total Citations
162
H-Index
7
About
Xiaoyi Cai is a leading researcher in off-road autonomy and multirobot coordination, whose work bridges the gap between safe navigation and real-world deployment. Her primary contributions lie in risk-aware motion planning for ground robots in unstructured environments, where she has pioneered methods that reason about both geometry and semantics—such as distinguishing traversable soft bushes from impassable logs. Her 2022 paper on learned speed distribution maps (49 citations) and the EVORA system for deep evidential traversability learning (36 citations) have become foundational references for risk-aware off-road navigation. Cai also made significant contributions to multirobot systems, co-developing the Robotarium—a free, remotely accessible multirobot testbed that has enabled hundreds of users worldwide to run thousands of experiments. Her work on long-distance robot team coordination, including an 11,000-km experiment between Georgia Tech and Tokyo Tech, and energy-aware information gathering for heterogeneous teams, demonstrates her ability to tackle large-scale, real-world challenges. With over 160 total citations and a pipeline of high-impact papers, Cai is shaping the future of autonomous navigation in complex, dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1Risk-Aware Off-Road Navigation via a Learned Speed Distribution Map49 citations · 2022
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- 3The Robotarium: Automation of a Remotely Accessible, Multi-Robot Testbed20 citations · 2021
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- 8A Sequential Composition Framework for Coordinating Multirobot Behaviors6 citations · 2020
- 9A Safety and Passivity Filter for Robot Teleoperation Systems3 citations · 2021
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