Douglas Chai

Edith Cowan University, Engineering (Italy)

Papers

13

Total Citations

767

H-Index

8

About

Douglas Chai is a prominent researcher whose work spans computer vision, robotics, and autonomous systems, with a particular focus on bridging perception and intelligent machine behavior. He has made significant contributions to the field through rigorous survey and review scholarship, most notably his widely cited 2018 review of deep learning methods in robotic grasp detection, which has accumulated over 260 citations across versions and remains a foundational reference for researchers tackling object manipulation challenges. His comprehensive review of fruit and vegetable classification techniques (192 citations) demonstrates his broader expertise in applied visual recognition, while his 2021 survey on teleoperation methods for mobile robots (162 citations) reflects a sustained interest in human-robot interaction and remote control enhancement. More recently, Chai has turned his attention to the demanding problem of autonomous navigation in unstructured outdoor environments, contributing a highly regarded 2023 review that has already garnered over 100 citations combined. His 2024 work on event cameras and neuromorphic computing applied to visual SLAM signals an exciting move toward next-generation sensing paradigms. Collectively, Chai's publications have accumulated over 700 citations, establishing him as an influential synthesizer and innovator in intelligent robotics research.

Research Focus

Key Achievements

8
H-Index
13
Papers
767
Total Citations
59
Avg Citations/Paper
🏆 Most Cited Paper
A comprehensive review of fruit and vegetable classification techniques
192 citations · 2018
📈 Most Prolific Year: 2018 (4 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Edith Cowan University, Engineering (Italy)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago