Andrew R. Barber
Papers
5
Total Citations
53
H-Index
4
About
Andrew R. Barber is a pioneering roboticist whose research focuses on autonomous navigation and inspection within confined, hazardous environments, particularly small-diameter pipe networks. His major contributions lie in developing miniaturized, tether-less robots that overcome the limitations of traditional inspection tools, which are often restricted by cable length, pipe size, and high operational costs. Barber’s most-cited work (29 citations) introduces a groundbreaking autonomous control system for these miniature robots, enabling them to navigate unknown pipe systems without human intervention. He further advanced the field with a non-assembly, 3D-printed walking mechanism that mimics a hexapod gait, drastically reducing design and assembly costs. His recent forays into TinyML-based feature detection (4 citations) equip these robots with on-board intelligence for real-time environmental perception, while the “Mega-Joey” platform (3 citations) demonstrates collaborative, autonomous infrastructure assessment. By integrating low-cost fabrication, machine learning, and swarm-like autonomy, Barber is redefining the possibilities for robotic inspection in critical infrastructure, promising safer, cheaper, and more efficient maintenance of sewer and pipe networks.
Research Focus
Key Achievements
Top Papers
- 1Autonomous control for miniaturized mobile robots in unknown pipe networks29 citations · 2022
- 2Non-assembly Walking Mechanism for Robotic In-Pipe Inspection11 citations · 2021
- 3Non-Assembly 3D-Printed Walking Mechanism Utilising a Hexapod Gait6 citations · 2022
- 4TinyML-Based In-Pipe Feature Detection for Miniature Robots4 citations · 2025
- 5