Dawei Dai

Shenzhen Institutes of Advanced Technology, Shenzhen Institute of Information Technology

Papers

Total Citations

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About

Dawei Dai is a robotics researcher whose work focuses on the practical challenges of autonomous mobile robot navigation and control. His key research areas include indoor surveillance robotics, path planning, and dynamic balance control. Dai's major contributions address fundamental problems in real-world robot deployment. His most cited work, "Detecting, locating and crossing a door for a wide indoor surveillance robot" (17 citations), tackles the difficult task of enabling large robots to autonomously navigate through narrow doorways using Kinect sensors—a critical capability for indoor patrol. He further advanced path planning with a novel method that simultaneously optimizes for robot posture and path smoothness (7 citations), addressing a gap in existing approaches. In the domain of dynamic control, Dai developed a learning-based intelligent control method using support vector regression for two-wheeled self-balancing robots (6 citations), demonstrating how machine learning can stabilize inherently unstable systems. His work bridges the gap between theoretical robotics and practical implementation, making autonomous robots more capable in real-world indoor environments.