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Evolutionary Robotics - Project ID SOC0023

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Evolutionary Robotics aims to apply evolutionary computation techniques to evolve the overall design or controllers, or both, for real and simulated autonomous robots. Numerous challenges exist that relate for example to (1) how to distribute intelligence between the body and brain (2) how to evolve robust behaviours that are tolerant to changes in the environment or the robot itself either in an individual robot or in a swarm of robots (3) the role of diversity in morphology/behaviour in contributing to robust behavior (4) how to “learn to learn”, i.e. evolve learning strategies that provide rapid learning in an adaptive environment.
A PhD candidate could focus on one or more of these areas: although some of the work would be undertaken in simulation, the student will also have access to a physical swarm of ~50 heterogeneous robots.

Academic qualifications
A first degree (at least a 2.1) ideally in Computer Science with a good fundamental knowledge of biologically inspired search algorithms for combinatorial optimisation and machine learning techniques.

English language requirement
IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:
• Experience of fundamental programming techniques such as C++, Python, Java
• Competent in data analysis and basic statistics
• Knowledge of bio-inspired methods for learning and optimisation
• Good written and oral communication skills
• Strong motivation, with evidence of independent research skills relevant to the project
• Good time management

Desirable attributes:
Experience with R, LaTeX, Linux is beneficial, as would be working with robot simulators such as VRep or Gazebo.

Edinburgh Napier University is committed to promoting equality and diversity in our staff and student community

Funding Notes

This is an unfunded position.


• Hart, Emma, Andreas SW Steyven, and Ben Paechter. "Evolution of a functionally diverse swarm via a novel decentralised quality-diversity algorithm." Proceedings of the Genetic and Evolutionary Computation Conference. ACM, 2018.
• Mouret, Jean-Baptiste, and Jeff Clune. "Illuminating search spaces by mapping elites." arXiv preprint arXiv:1504.04909(2015).
• Cully, Antoine, et al. "Robots that can adapt like animals." Nature 521.7553
(2015): 503.
• Silva, Fernando, et al. "Open issues in evolutionary robotics." Evolutionary
computation 24.2 (2016): 205-236.
• Nolfi, Stefano, et al. "Evolutionary robotics." Springer Handbook of Robotics.
Springer, Cham, 2016. 2035-2068.
• Doncieux, Stephane, et al. "Evolutionary robotics: what, why, and where
to." Frontiers in Robotics and AI 2 (2015): 4.

Related Subjects

How good is research at Edinburgh Napier University in Computer Science and Informatics?

FTE Category A staff submitted: 10.70

Research output data provided by the Research Excellence Framework (REF)

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