From skylight input to behavioural output: A computational model of the insect polarised light compass
Fig 12
Behavioural simulation for the path integration task.
Testing the celestial compass on path integration tasks. We set up the experiments to take place at 10am in Seville, Spain (37°23′33.03′′N, 5°53′01.95′′W). The altitude variance is 0.8 m and the maximum tilting angle noticed in all the experiments is δ = 47°. (A) Five representative routes of ants in different sky disturbance levels for an even [(B) uneven] terrain and their respective inward paths; different colours are for different disturbance levels (see legend); the faded lines are the outward paths and the bold ones are the inward. (C) The uneven terrain map; green colour denote hills and purple valleys; the marked region is the one cropped for the A and B plots. (D) Deviation from the best possible route during homing for different disturbance levels for even [(E) uneven] terrain. We scale up our experimental arena (by a factor of 120) to enable longer runs that demonstrate the performance of the time compensation mechanism. (F) Comparison of the path integration performance in terms of tortuosity with (solid black line) and without using the time compensation mechanism (dashed line). (G) The actual paths generated by the above experiment; green arrows show the direction of the sun at the beginning (10:00 am, 103.65° clockwise from north) and end of the route (11:16 am, 127.47° clockwise from north).