Mapping Unknown Environments With Instrumented Honey Bees

Recent innovations in miniature sensors are driving a shift from robotic to bio-hybrid systems for exploration of unstructured environments. The ubiquity of honey bees in modern agriculture and ecology along with their superior agility, olfactory sense, and collective foraging skills make them a promising complement to traditional robots. This paper explores the potential of such systems based on a custom honey bee foraging simulator and models of state-of-the art miniature flight recorders which can measure solar heading at regular time intervals, as well as exploratory data collected from the sensor mounted on an autonomous quadrotor. The size and functionality of the sensor is heavily influenced by its memory footprint, therefore, we investigate the impact of sensor sampling time on map accuracy. Our results indicate that a sampling rate down to 5Hz can be used to sense obstacle locations in a 5-acre field with an accuracy corresponding to 70% of the obstacle radius, and within 4% of its true area. This technique shows promise for using instrumented honey bees to map and monitor unstructured environments which are difficult or costly for robots to robustly navigate, monitor, and map.