After completing undergraduate degrees in pure mathematics and mechatronic engineering at the University of Adelaide, I became interested in biologically-inspired robotic systems. I pursued a PhD in the Centre for Visual Sciences at the Australian National University, looking at the visual tracking behaviour of dragonflies. I completed my doctoral work in 2007, under the supervision of Professor Jochen Zeil. Since 2009 I have held a post-doctoral research position in the Centre of Excellence in Cognitive Interaction Technology at the University of Bielefeld (CITEC). I am interested in any and all bio-inspired systems, sensors and mechanics, but recently have been focusing most on visual navigation strategies and flight control.

Polarisation vision

Update! Filming at the DLR, with our sensors on board the test quadrocopter.

Many insects possess the ability to detect the directional component of light, what we term its polarisation properties. The dorsal rim area, in particular, is strongly sensitive to the direction of polarisation (the phase) of incoming light, and is thought to be used for navigational purposes.

The compound eye of an insect is made up of many ommatidia, which include a lens, cornea, and photoreceptor cells. Each ommatidium has its own 'preferred' orientation - this is the direction of polarisation which it responds most strongly to. By comparing signals coming from ommatidia with different preferred orientations, but which view the same area of the sky, the insect can create a 'map' of the polarisation properties of the incoming light.

When light originating from the sun hits our atmosphere, it results in a distinctive 'pattern' of different polarisation orientations and magnitudes. This pattern can be used as a sun-compass, giving us the ability to detect the position of the sun even on overcast days, or where the sun is invisible due to environmental features, eg. under a forest canopy. Other environment features, like water, or particular kinds of vegetation, can also be distinguished by their polarisation properties.

One of our early insect-
inspired wide-field visual sensors

Insects have often been the inspiration for engineered solutions to common problems. They have evolved highly parsimonious yet sophisticated solutions to biomechanical problems, like long-distance navigation, flight stabilisation, or motility over highly variable terrain. We are developing lightweight visual sensors which mimic features of the insect compound eye, in order to understand and imitate their extraordinary capabilities.

Related downloads: some useful Matlab functions for analysing the polarisation properties of natural scenes.

Tracking and pursuit

Autonomous tracking of objects in a moving scene is no easy task for a computer, especially keeping track of multiple similar-looking items. Research into insect pursuit, tracking and homing behaviours can help us find useful strategies. For example, satellite flies track food-laden digger wasps in order to lay their eggs in the prey brought back to the wasp's nest. They must be very precise and fast, in order to swoop in behind the wasp at the appropriate moment, without being spotted. Analysis of their flight behaviour reveals a finely tuned control system ready to respond almost instantly to the subtlest of signals.

Dragonflies demonstrate amazing aerobatic ability in their conspecific pursuit flights, seen during territorial disputes between males. And yet these complex flight patterns are generated by relatively simply control mechanisms, applied to an unfolding dynamic 3-dimensional scene.

Related downloads

BeeTrackerGUI, a matlab toolbox with a graphical interface designed to track moving objects such as insects in a natural environment.

LocustWingBeatTracker - developed to analyse the dynamics of the wing beats of tethered locusts, this set of functions is more appropriate for video of fast but repetitive movement by a high-contrast object.


  • made a little light following robot but he keeps running into walls and knocking his top off.
  • training NN (LLM) for sky pattern recognition
  • haptics talk by Heinrich Bülthoff
  • modelling first-order neuronal response of locust DRA ommatidia