TY - JOUR

T1 - Biologically inspired herding of animal groups by robots

AU - King, Andrew J.

AU - Portugal, Steven J.

AU - Strombom, Daniel

AU - Mann, Richard P.

AU - Carrillo, Jose A.

AU - Kalise, Daniel

AU - Croon, Guido de

AU - Barnett, Heather

AU - Scerri, Paul

AU - Gross, Roderich

AU - Chadwick, Dave

AU - Papadopoulou, Marina

PY - 2023/2/1

Y1 - 2023/2/1

N2 - A single sheepdog can bring together and manoeuvre hundreds of sheep from one location to another. Engineers and ecologists are fascinated by this sheepdog herding because of the potential it provides for ‘bio-herding’: a biologically inspired herding of animal groups by robots. Although many herding algorithms have been proposed, most are studied via simulation.There are a variety of ecological problems where management of wild animal groups is currently impossible, dangerous and/or costly for humans to manage directly, and which may benefit from bio-herding solutions.Unmanned aerial vehicles (UAVs) now deliver significant benefits to the economy and society. Here, we suggest the use of UAVs for bio-herding. Given their mobility and speed, UAVs can be used in a wide range of environments and interact with animal groups at sea, over the land and in the air.We present a potential roadmap for achieving bio-herding using a pair of UAVs. In our framework, one UAV performs ‘surveillance’ of animal groups, informing the movement of a second UAV that herds them. We highlight the promise and flexibility of a paired UAV approach while emphasising its practical and ethical challenges. We start by describing the types of experiments and data required to understand individual and collective responses to UAVs. Next, we describe how to develop appropriate herding algorithms. Finally, we describe the integration of bio-herding algorithms into software and hardware architecture.

AB - A single sheepdog can bring together and manoeuvre hundreds of sheep from one location to another. Engineers and ecologists are fascinated by this sheepdog herding because of the potential it provides for ‘bio-herding’: a biologically inspired herding of animal groups by robots. Although many herding algorithms have been proposed, most are studied via simulation.There are a variety of ecological problems where management of wild animal groups is currently impossible, dangerous and/or costly for humans to manage directly, and which may benefit from bio-herding solutions.Unmanned aerial vehicles (UAVs) now deliver significant benefits to the economy and society. Here, we suggest the use of UAVs for bio-herding. Given their mobility and speed, UAVs can be used in a wide range of environments and interact with animal groups at sea, over the land and in the air.We present a potential roadmap for achieving bio-herding using a pair of UAVs. In our framework, one UAV performs ‘surveillance’ of animal groups, informing the movement of a second UAV that herds them. We highlight the promise and flexibility of a paired UAV approach while emphasising its practical and ethical challenges. We start by describing the types of experiments and data required to understand individual and collective responses to UAVs. Next, we describe how to develop appropriate herding algorithms. Finally, we describe the integration of bio-herding algorithms into software and hardware architecture.

U2 - 10.1111/2041-210X.14049

DO - 10.1111/2041-210X.14049

M3 - Article

VL - 14

SP - 478

EP - 486

JO - Methods in Ecology and Evolution

JF - Methods in Ecology and Evolution

SN - 2041-210X

IS - 2

ER -