Xiangrui Kong
Papers
2
Total Citations
11
H-Index
2
About
Xiangrui Kong is an emerging researcher at the intersection of embodied artificial intelligence, mobile robotics, and large language models (LLMs). His work focuses on harnessing the reasoning capabilities of LLMs to advance autonomous robotic systems, with particular emphasis on coverage path planning and the security vulnerabilities inherent in LLM-integrated platforms. In his 2025 paper, Kong proposed a novel LLM-embodied path planning framework utilizing the EyeSim simulation environment, demonstrating how state-of-the-art language models can be leveraged to solve complex, high-level navigation challenges for mobile agents — a contribution that has already attracted 6 citations. Complementing this, his 2024 investigation into prompt injection attacks against LLM-integrated mobile robotic systems — garnering 5 citations — highlights a critical and often overlooked dimension of deploying multimodal AI in real-world robotics: security. By exposing how malicious prompt manipulation can compromise systems powered by models such as GPT-4o, Kong has made a timely contribution to the responsible development of embodied AI. Though early in his career, his research is positioning him as a thoughtful voice in both the capabilities and the safe deployment of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2