Michael Garvie

Papers

Total Citations

H-Index

About

Michael Garvie is a pioneering researcher at the University of Sussex, whose work sits at the intersection of evolutionary robotics, bio-inspired design, and embodied artificial intelligence. His research fundamentally explores how physical hardware—rather than just software—can be evolved to create adaptive, autonomous robots. Garvie’s most notable contribution is his groundbreaking 2020 study, in which he became the first researcher to successfully evolve robot control circuits directly on a field programmable transistor array (FPTA) in analog hardware. This achievement allowed a physical robot to incrementally learn visually guided behaviors, such as target finding, marking a significant step toward truly embodied AI. His highly cited 2021 review, “Recent advances in evolutionary and bio-inspired adaptive robotics,” synthesizes these developments and has garnered 36 citations, reflecting its influence in the field. By exploiting the dynamics of physical hardware, Garvie challenges conventional software-centric approaches, offering a more robust and efficient path for autonomous systems. His work is essential reading for anyone interested in how evolution and embodiment can reshape the future of robotics.