All posts by klagogia

Methodological issues

The essence of our methodology is to use robots as models of biological systems.  We usually refer to this as “Biorobotics” (although the terminology in this field is not fixed). An important feature is that our principal focus is on understanding the biology, using robotics as a tool, rather than on trying to improve robotics or address specific robot applications. However the fact that biological systems are capable of many things that we would like robots to be capable of – such as adaptive interaction with real complex environments to achieve tasks robustly – means that results of the work are likely to have some benefit for robotics as well.

Nevertheless, our main motivation is to understand brains and behaviour. We focus on insect systems because there is a better chance that we can understand and model the complete processing loop, at a neural level, in these ‘simpler’ systems. We use robots because this forces us to consider the whole loop, including the physics of interaction with the environment.

As this is a relatively novel methodology, it is important to understand how it fits into scientific explanation, and this has been the focus of some of our research. For example, any scientific modelling requires decisions about abstraction, about the level of mechanisms to model, about the scope of systems to be explained, about the accuracy with which mechanisms will be reproduced, about the medium that will be used to implement the model, and the criteria for evaluation.

Key publications

  • Webb, B (2000) What does robotics offer animal behaviour? Animal Behaviour, 60, 545-558 (pdf preprint)
  • Webb, B. (2001) Can robots make good models of biological behaviour? Target article for Behavioural and Brain Sciences 24 (6) 1033-1050 (html preprint)
  • Webb,B. and Consi, T.  eds. (2001)  Biorobotics: methods and applications AAAI Press
  • Webb, B. (2002) Robots in invertebrate neuroscience. Nature 417:359-363 (pdf preprint)
  • Webb, B. (2006) Validating biorobotic models. Journal of Neural Engineering 3 R25-R35 doi:10.1088/1741-2560/3/3/R01 (pdf preprint)

Learning in Drosophila

Adult fruit-flies can learn to avoid odours that are paired with shock, and larval fruit-flies will learn to avoid or approach odours that are paired with attractive or unattractive food. We are modelling the brain circuits underlying these changes in behaviour.

Ant navigation

Desert ants forage individually (without chemical trails) and can reliably return to their nest or a food source over long distances in cluttered environments. We are studying these behaviours in the ants and building computational models.