Ruiqing Chen
Papers
1
Total Citations
23
H-Index
1
About
Ruiqing Chen is a pioneering researcher in Human-Robot Interaction (HRI) and multimodal robotic systems, with a focus on socially-aware navigation and intuitive human-robot communication. His most cited work, "Language and Sketching: An LLM-driven Interactive Multimodal Multitask Robot Navigation Framework" (2024, 23 citations), introduces a groundbreaking framework that integrates large language models with sketching interfaces to enable robots to understand and execute complex, context-rich commands. This innovation addresses a critical gap in HRI by allowing robots to seamlessly switch between tasks like point-to-point navigation, human-following, and guiding, all while adeptly avoiding obstacles in dynamic environments. Chen’s contributions are particularly notable for bridging the gap between natural language instructions and physical robot actions, making robotic systems more accessible and versatile. His work has already garnered attention for its potential to transform assistive robotics and autonomous navigation. By combining LLM-driven reasoning with multimodal inputs, Chen is shaping the future of intuitive, adaptive human-robot collaboration, paving the way for robots that can truly understand and respond to human intent in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1