Daqign Yi
Papers
1
Total Citations
7
H-Index
1
About
Daqing Yi is a researcher whose work lies at the intersection of robotics, human-robot interaction, and autonomous decision-making. His primary research areas include path planning under human constraints, multi-agent coordination, and information-driven robotics. Yi’s most cited paper, “Informative Path Planning with a Human Path Constraint” (2014, 7 citations), introduces a novel framework where humans specify soft constraints on a robot’s trajectory, enabling collaborative search tasks. The paper presents an anytime algorithm that allows robots to optimize their paths while respecting human directives, balancing autonomy with human oversight—a critical contribution to shared-control systems. This work has influenced subsequent studies in human-robot teaming and adaptive planning. Yi’s broader impact is seen in his contributions to robotics and AI, where his methods improve how robots reason under uncertainty and interact with humans. His research is particularly relevant for applications in search-and-rescue, environmental monitoring, and assistive robotics. With a focus on practical, real-time solutions, Yi continues to advance the field of human-aware autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Informative path planning with a human path constraint7 citations · 2014