Papers
21
Total Citations
201
H-Index
8
About
Daokui Qu is a robotics researcher whose work spans mobile robot navigation, motion planning, human-robot interaction, and legged locomotion. Over nearly two decades, he has made sustained contributions to some of the most practically demanding challenges in robotics, from enabling autonomous navigation in GPS-denied outdoor environments to developing real-time collision avoidance strategies for safe human-robot collaboration. Qu's early work introduced hybrid path planning strategies for dynamic indoor environments, combining global A* methods with reactive local planners — an approach that garnered 25 citations and laid groundwork for subsequent navigation research. His trajectory planning contributions, particularly asymmetric S-curve profiling for precision motion control, have found application in both industrial manipulators and vacuum robots, addressing critical needs for smooth, vibration-minimized movement. His 2019 work on quadrupedal whole-body motion control using centroidal momentum dynamics reflects a broadening research vision into dynamic legged systems, accumulating 20 citations. More recently, Qu has tackled real-time collision avoidance and time-optimal multi-point trajectory generation, demonstrating a continued relevance to cutting-edge robotics challenges. With a citation record spanning foundational mobile robotics to advanced manipulation and legged locomotion, Qu represents a versatile and enduring contributor to intelligent robotic systems research.
Research Focus
Key Achievements
Top Papers
- 1
- 2A hybrid approach for mobile robot path planning in dynamic environments25 citations · 2007
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- 6Asymmetric s-curve trajectory planning for robot point-to-point motion13 citations · 2009
- 7Asymmetric trajectory planning for vacuum robot motion9 citations · 2011
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