Papers
8
Total Citations
105
H-Index
6
About
Canzhi Guo is a robotics and automation researcher whose work spans two primary domains: robotic non-destructive testing (NDT) systems and intelligent robotic manipulation. With a cumulative body of work drawing over 100 citations, Guo has made meaningful contributions to advancing automated inspection and smart robotic systems. Guo's most recognized research focuses on ultrasonic NDT for composite workpieces with complex curved surfaces, particularly using dual-robot configurations. His 2019 papers on dual-robot testing systems (29 and 16 citations respectively) introduced innovative approaches to tool centre point calibration and trajectory planning, addressing the pressing industrial challenge of inspecting semi-enclosed composite structures with precision and reliability. A further contribution on air-coupled ultrasonic testing (10 citations) refined probe alignment accuracy, strengthening the practical viability of robotic inspection workflows. Beyond NDT, Guo has demonstrated versatility through research in agricultural robotics, developing an improved YOLO v4 model for grape detection in unstructured environments (25 citations), and in soft robotics, designing magnetic soft robots capable of rolling and grasping (11 citations) alongside novel soft end effectors for robotic picking tasks. Together, these contributions reflect a researcher committed to bridging intelligent sensing, computer vision, and advanced robotic design across diverse real-world applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2An improved YOLO v4 used for grape detection in unstructured environment25 citations · 2023
- 3
- 4A magnetic soft robot with rolling and grasping capabilities11 citations · 2022
- 5
- 6Tool Frame Calibration for Robot-Assisted Ultrasonic Testing7 citations · 2023
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- 8