Papers
4
Total Citations
18
H-Index
3
About
Chaoke Guo is a robotics researcher whose work focuses on the intersection of civil infrastructure automation and intelligent robotic systems. His primary research areas include motion planning, sensor-based coverage, and robotic manipulation for infrastructure rehabilitation. Guo’s major contributions center on developing optimal control strategies for crack-filling robots, where he pioneered a complete and near-optimal path planning approach that simultaneously handles sensor-based inspection and footprint coverage—a significant advancement for autonomous repair of roads and bridge decks. His 2017 paper on optimal motion planning for crack-filling robots has garnered 6 citations, while his 2019 work on simultaneous inspection and coverage planning has received 5 citations, reflecting growing interest in this niche. Beyond crack filling, Guo has explored high-speed bionic mechanical leg design and rotary percussive drilling for robotic rehabilitation, demonstrating versatility in applying robotics to real-world civil challenges. His research is notable for bridging theoretical planning algorithms with practical deployment, offering solutions that could dramatically improve the efficiency and safety of infrastructure maintenance.
Research Focus
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Top Papers
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