Papers
19
Total Citations
349
H-Index
10
About
Alan G. Millard is a distinguished researcher whose work spans neuromorphic computing, fault-tolerant systems, and swarm robotics — fields at the fascinating intersection of biology-inspired computation and autonomous systems engineering. His most influential contributions center on the development of self-repairing neural networks that draw inspiration from biological mechanisms. His 2017 paper on homeostatic fault tolerance in spiking neural networks (58 citations) and his 2018 work on astrocyte-neural network coupling (50 citations) demonstrate his pioneering role in translating biological self-repair principles into robust computational architectures. Millard has equally shaped the field of swarm robotics, developing practical tools and methodologies for fault detection, diagnosis, and system analysis. His ARDebug augmented reality debugging tool, adaptive fault diagnosis framework, and runtime fault detection approaches collectively address one of swarm robotics' most persistent challenges: maintaining reliable collective behavior when individual robots fail. His Pi-puck extension board (28 citations) reflects a hands-on engineering ethos, democratizing advanced robotics research through accessible, low-cost hardware. With over 290 cumulative citations across his top works, Millard's research has had meaningful impact on both the theoretical foundations and practical implementation of resilient autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Exploring Self-Repair in a Coupled Spiking Astrocyte Neural Network50 citations · 2018
- 3
- 4Towards Exogenous Fault Detection in Swarm Robotic Systems29 citations · 2014
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- 8Adaptive Online Fault Diagnosis in Autonomous Robot Swarms21 citations · 2018
- 9
- 10A low-cost real-time tracking infrastructure for ground-based robot swarms12 citations · 2014