Robot Talk

Episode Thirteen – Robot evolution: survival of the fittest


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Unlike the characteristics of most robots, the adaptations of living organisms weren't designed - they evolved through natural selection over millions of years. Evolutionary robotics takes inspiration from this process of natural selection to create new robot designs, and allow robots to adapt to their environment over many generations.

In the first episode of 2022, I'll be chatting to three roboticists about robot evolution and adaptation: Dr Edgar Buchanan (University of York), Prof Fumiya Iida (University of Cambridge), and Dr Hemma Philamore (University of Bristol).

Edgar Buchanan is a Research Associate in Evolutionary Robotics working as part of the Autonomous Robot Evolution project at the University of York. He is conducting research into the autonomous design and fabrication of robots through the use of evolutionary algorithms. He has a master's degree in Autonomous Robot Engineering and a PhD degree in Swarm Robotics from the University of York. In 2016, he won "Kathleen Mary Stott Memorial Prize for excellence in scientific research" at the University of York.

Fumiya Iida is a Professor of Robotics at the University of Cambridge. While he worked as a postdoctoral associate at the Computer Science and Artificial Intelligence Laboratory at Massachusetts Institute of Technology, he was awarded the Fellowship for Prospective Researchers from the Swiss National Science Foundation, and then, the Swiss National Science Foundation Professorship hosted by ETH Zurich. In 2014 he moved to the University of Cambridge as the director of Bio-Inspired Robotics Laboratory.

Hemma Philamore is a Lecturer in Robotics at the University of Bristol and is based at the Bristol Robotics Lab. Her research is about environmental robots that function as part of natural ecosystems and the social ecosystems we create as humans. Her work includes soft robotics, bio-inspired and bio-hybrid robots, bio-electrical systems for power and sensing and human-robot-interaction.

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