Andrew Starr
Papers
11
Total Citations
158
H-Index
8
About
Andrew Starr is a researcher whose work sits at the intersection of robotics, autonomous systems, and railway infrastructure maintenance. Over more than two decades, he has made sustained contributions to the development of intelligent, automated solutions for industrial and transport applications — from early work on robot failure analysis in automotive production lines (1999, 14 citations) to pioneering research on autonomous railway inspection and repair systems. Starr's most significant recent contributions focus on transforming how railways are maintained. His work on rail-road amphibious robotic systems, mobile manipulators, and 3D track reconstruction using robotic vision addresses the high costs and safety risks of human-dependent maintenance operations. His widely cited review of localisation and navigation technologies for autonomous railway systems (2022, 25 citations) has become a key reference in the field, while his 2023 paper on track reconstruction using robotic vision has already accumulated 37 citations, signalling strong community uptake. Collectively, his research advocates for smarter, safer, and more efficient railway maintenance through sensor fusion, autonomous navigation, and AI-driven diagnostics. Starr's body of work offers students and engineers a comprehensive foundation for understanding how robotics is reshaping critical infrastructure management worldwide.
Research Focus
Key Achievements
Top Papers
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- 4Towards an Autonomous RIRS: Design, Structure Investigation and Framework14 citations · 2021
- 5Failure analysis of mature robots in automated production14 citations · 1999
- 6An Overview of Web Robots Detection Techniques11 citations · 2020
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