EVOLUTION OF SENSORIMOTOR NEURAL NETWORKS TO PERFORM ACTIVE MOTION CAMOUFLAGE
Project funded by EPSRC
The objectives of this project may be summarised as follows;
· To develop the first explicit neural model for active motion camouflage.
· Determination of the optimal, biologically plausible, sensorimotor neural architectures and learning rules for a system to achieve active motion camouflage.
· Visualisation of the behaviour of the best performing motion camouflage sensorimotor systems.
As the prey, denoted by the dark circles in the figure on the left, passed by a genuine fixed point in the environment, P, the lines of sight connecting the prey’s eyes to this point determine the set of constraint lines which define the optic flow characteristic of a stationary object. Camouflage may be accomplished by ensuring that the predator's trajectory, shown by the textured circles, is such that it always moves so that it lies along a set of constraint lines consistent with some chosen fixed position in the environment. This selected position can be anywhere along the initial camouflage constraint line, that is the line joining the initial positions of predator and prey. The camouflage trajectory may be achieved by requiring that at each stage of the approach the predator moves to ensure that it consistently views the prey frontally and moves radially away from its initial position, so moving forwards along the camouflage constraint lines. This strategy ensures that as the approach is made the predator’s image, projected onto the prey’s retina, is the same as would arise from the predator remaining stationary at its initial position. The first requirement, of viewing the prey frontally, requires the predator to be able to co-ordinate sensory visual input with motor output to correct orientation. To achieve the second requirement, that of a strictly radial movement towards the prey, the predator must learn to co-ordinate the angular movements required by the orienting step with corrective lateral motions such that the ratio of the two is a constant, and equal to the distance from the initial position.