Alex Dewar
Papers
6
Total Citations
83
H-Index
5
About
Alex Dewar is a robotics researcher based at the University of Sussex whose work sits at the intersection of biological intelligence and autonomous systems. Specialising in bio-inspired and evolutionary approaches to robotics, Dewar has made significant contributions to the field of visual navigation, drawing inspiration from the remarkable navigational capabilities of insects to develop lightweight, efficient algorithms suitable for real-world robotic deployment. His most influential work, "Recent Advances in Evolutionary and Bio-Inspired Adaptive Robotics" (2021, 36 citations), provides a comprehensive survey of cutting-edge developments emerging from the Sussex group, highlighting how embodied dynamics can be exploited to produce adaptive autonomous behaviour. A recurring theme across his research is the application of familiarity-based neural network models to robot navigation — work demonstrated convincingly in real-world environments and extended to three-dimensional flight scenarios for aerial robots. His 2019 paper on single-layer network route encoding (17 citations) is particularly noteworthy for bridging simulation results with physical robot deployment. Through explorations of wavelet-domain snapshot navigation and robustness testing across varied conditions, Dewar has helped establish insect-inspired visual navigation as a credible and practical paradigm for next-generation autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Insect-Inspired Visual Navigation for Flying Robots15 citations · 2016
- 4
- 5Snapshot Navigation in the Wavelet Domain5 citations · 2020
- 6