What can be learnt from analysing insect orientation flights using probabilistic SLAM?
In this paper, we provide an analysis of orientation flights in bumblebees, employing a novel technique based on simultaneous localisation and mapping (SLAM) a probabilistic approach from autonomous robotics. We use SLAM to determine what bumblebees might learn about the locations of objects in the world through the arcing behaviours that are typical of these flights. Our results indicate that while the bees are clearly influenced by the presence of a conspicuous landmark, there is little evidence that they structure their flights to specifically learn about the position of the landmark.
Baddeley
Bartholomew
B
Department of Informatics, Centre for Computational Neuroscience and Robotics, University of Sussex, Brighton, UK. bartbaddeley@googlemail.com
Philippides
Andrew
A
Graham
Paul
P
de Ibarra
Natalie Hempel
NH
Collett
Thomas
T
Husbands
Phillip
P
D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D001516:Bees / Q000502:physiology*; D001522:Behavior, Animal / Q000502:physiology; D001921:Brain / Q000502:physiology; D003198:Computer Simulation; D005106:Exploratory Behavior / Q000502:physiology; D005260:Female; D005426:Flight, Animal / Q000502:physiology*; D007858:Learning / Q000502:physiology*; D008432:Mathematical Computing; D055641:Mathematical Concepts; D008568:Memory / Q000502:physiology; D023421:Models, Animal; D015233:Models, Statistical; D009949:Orientation / Q000502:physiology*; D012371:Robotics / Q000379:methods; D013028:Space Perception / Q000502:physiology*; D013045:Species Specificity; D014794:Visual Fields / Q000502:physiology; D014796:Visual Perception / Q000502:physiology