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30 May 2022 Obstacle avoidance and navigation in honeybees
Sridhar Ravi, Fumin Zhang
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Abstract
Insects are well known to be adept at flying through cluttered natural environments. This ability to avoid collisions and control flight speed is an active field of interest for potential applications in unmanned aerial vehicles. Previous studies have shown that insects primarily rely on visual motion of the environment, known as optic flow, to perform flight manoeuvres such as course control, landing, terrain following, etc. Vision based flight behaviours of honeybees have been studied extensively in the past and have been explained in terms of either the optomotor response or the collision avoidance (centering) response. However, the strategies used for avoiding smaller objects in the frontal view field remain unclear. This study investigates the strategies being used by honeybees (Apis Milfera) to avoid such obstacles. This was done by performing behavioural experiments, where the bees were trained to fly in a tunnel and were then presented with cylindrical obstacles of six different sizes ranging from 25mm to 165mm. The flights were recorded using a GoPro camera and then digitised using Matlab. The digitised trajectories have then been analysed for cues such as retinal angle, relative retinal expansion velocity(RREV), optic flow, etc., to gain an insight into the visuo-motor strategies being implemented by honeybees to avoid these obstacles. Our findings, based on analysing major events during flight, such as the point of deceleration before the obstacle, the point of maximum curvature and the point where bees cross the obstacle, suggest a combination of RREV and optic flow based response to avoid these obstacles.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sridhar Ravi and Fumin Zhang "Obstacle avoidance and navigation in honeybees", Proc. SPIE PC12124, Unmanned Systems Technology XXIV, PC1212408 (30 May 2022); https://doi.org/10.1117/12.2634272
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