Speaker: Prof. Emma Hart, Edinburgh Napier University

Title: An Evolutionary Approach to the Autonomous Design and Fabrication of Robots in Unknown Environments

The design is traditionally the domain of humans – engineers, physicists, and increasingly AI experts. However, if the robot is intended to operate in a completely unknown environment (for example, to clean up inside a nuclear reactor), it is very difficult for human designers to predict what kind of robot might be required. Evolutionary computing has been applied in various aspects of robotics for many years, for example, to design controllers or body plans. When coupled with advances in materials and printing technologies that allow rapid prototyping in hardware, it offers a potential solution to the issue raised above, for example, enabling colonies of robots to evolve and adapt over long periods of time while situated in the environment they have to work in. However, it also brings new challenges from both an algorithmic and an engineering perspective.

The additional constraints introduced by the need, for example, to manufacture robots autonomously, explore rich morphological search spaces and develop novel forms of control require some re-thinking of “standard’ approaches in evolutionary computing, particularly on the interaction between evolution and individual learning. I will discuss some of these challenges and propose and showcase some methods to address them that have been developed during the ARE project. Finally, I will touch on some ethical issues associated with the notion of autonomous robot design and discuss the potential of artificial evolution to be used as a tool to gain new insights into biological evolving systems.

Bio:

Professor Emma Hart has worked in the field of Evolutionary Computing for over 20 years on a range of applications ranging from combinatorial optimisation to robotics, where the latter includes robot design and swarm robotics. Her current work is mainly centred in Evolutionary Robotics, bringing together ideas on using artificial evolution as a tool for optimisation with research that focuses on how robots can be made to continually learn, improving performance as they gather information from their own or other robots’ experiences. The work has attracted significant media attention, including recently in the New Scientist and the Guardian. She gave a TED talk on this subject at TEDWomen in December 2021 in Palm Springs, the USA, which has attracted over ~1.5 million views since being released online in April 2022.  She is the Editor-in-Chief of the journal Evolutionary Computation (MIT Press) and an elected member of the ACM SIG on Evolutionary Computing.   In 2022, she was honoured to be elected as a Fellow of the Royal Society of Edinburgh for her contributions to the field of Computational Intelligence.

THUR 29th SEPTEMBER 4 PM – 5 PM AEST

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