Will biomimetic robots be able to change a hivemind to guide honeybees’ ecosystem services?

Abstract

We study whether or not a group of biomimetic waggle dancing robots is able to significantly influence the swarm-intelligent decision making of a honeybee colony, e.g., to avoid foraging at dangerous food patches using a mathematical model. Our model was successfully validated against data from two empirical experiments: one examined the selection of foraging targets and the other cross inhibition between foraging targets. We found that such biomimetic robots have a significant effect on a honeybee colony’s foraging decision. This effect correlates with the number of applied robots up to several dozens of robots and then saturates quickly with higher robot numbers. These robots can reallocate the bees’ pollination service in a directed way towards desired locations or boost it at specific locations, without having a significant negative effect on the colony’s nectar economy. Additionally, we found that such robots may be able to lower the influx of toxic substances from potentially harmful foraging sites by guiding the bees to alternative places. These effects also depend on the saturation level of the colony’s nectar stores. The more nectar is already stored in the colony, the easier the bees are guided by the robots to alternative foraging targets. Our study shows that biomimetic and socially immersive biomimetic robots are a relevant future research target in order to support (a) the bees by guiding them to safe (pesticide free) places, (b) the ecosystem via boosted and directed pollination services and (c) human society by supporting agricultural crop pollination, thus increasing our food security this way.

Animal–robot interaction—an emerging field at the intersection of biology and robotics

“…robots interacting with social or eusocial animals. In this special issue, the work by Lazic and Schmickl [17] investigates how a group of waggle-dance imitating biomimetic robots could alter the hive-mind of collective foraging decisions of a honeybee colony and analysis. Using an extended version of a conglomerate of several state-of-the-art honeybee nectar foraging models [18][19][20][21][22] the authors investigate if such robots can lead a colony to revert a previously made collective foraging decision and how many robots it would take to operate in a beehive.…”

“…Also lab mice and other rodents interact with robots, some of them rather biomimetic [29], others not so [30]. Thirdly, ARIS and ORIS enable novel minimum-stress methods in agriculture and livestock management [17,31]. Finally, such agents open the door to novel ecological monitoring and ecosystem-management strategies [32,33], if the agents interact with organisms in the wild, in agro-ecosystems or in other dedicated structures (e.g.…”