A Vision-based System for Social Insect Tracking

Abstract

Socia1 insects, especially honeybees, play an essential role in nature, and their recent decline threatens the stability of many ecosystems. The behaviour of social insect colonies is typically governed by a central individual, e.g., by the honeybee queen. The RoboRoyale project aims to use robots to interact with the queen to affect her behaviour and the entire colony’s activity. This paper presents a necessary component of such a robotic system, a method capable of real-time detection, localisation, and tracking of the honeybee queen inside a large colony. To overcome problems with occlusions and computational complexity, we propose to combine two vision-based methods for fiducial marker localisation and tracking. The experiments performed on the data captured from inside the beehives demonstrate that the resulting algorithm outperforms its predecessors in terms of detection precision, recall, and localisation accuracy. The achieved performance allowed us to integrate the method into a larger system capable of physically tracking a honeybee queen inside its colony. The ability to observe the queen in fine detail for prolonged periods of time already resulted in unique observations of queen-worker interactions. The knowledge will be crucial in designing a system capable of interacting with the honeybee queen and affecting her activity.