TY - JOUR
T1 - Robotic herding of a flock of birds using an unmanned aerial vehicle
AU - Paranjape, Aditya A.
AU - Chung, Soon-Jo
AU - Kim, Kyunam
AU - Shim, David Hyunchul
N1 - Funding Information:
Manuscript received October 12, 2017; revised April 4, 2018; accepted April 7, 2018. Date of publication August 2, 2018; date of current version August 15, 2018. This paper was recommended for publication by Guest Editor P. Dames and Editor F. Park upon evaluation of the reviewers’ comments. This work was supported in part by the National Science Foundation CAREER Award NSF IIS 1253758 & 1664186 and in part by the California Institute of Technology. (Corresponding author: Soon-Jo Chung.) A. A. Paranjape is with the Department of Aeronautics, Imperial College London, London SW7 2AZ, U.K. (e-mail:,[email protected]).
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2018/8
Y1 - 2018/8
N2 - In this paper, we derive an algorithm for enabling a single robotic unmanned aerial vehicle to herd a flock of birds away from a designated volume of space, such as the air space around an airport. The herding algorithm, referred to as the m-waypoint algorithm, is designed using a dynamic model of bird flocking based on Reynolds' rules. We derive bounds on its performance using a combination of reduced-order modeling of the flock's motion, heuristics, and rigorous analysis. A unique contribution of the paper is the experimental demonstration of several facets of the herding algorithm on flocks of live birds reacting to a robotic pursuer. The experiments allow us to estimate several parameters of the flocking model, and especially the interaction between the pursuer and the flock. The herding algorithm is also demonstrated using numerical simulations.
AB - In this paper, we derive an algorithm for enabling a single robotic unmanned aerial vehicle to herd a flock of birds away from a designated volume of space, such as the air space around an airport. The herding algorithm, referred to as the m-waypoint algorithm, is designed using a dynamic model of bird flocking based on Reynolds' rules. We derive bounds on its performance using a combination of reduced-order modeling of the flock's motion, heuristics, and rigorous analysis. A unique contribution of the paper is the experimental demonstration of several facets of the herding algorithm on flocks of live birds reacting to a robotic pursuer. The experiments allow us to estimate several parameters of the flocking model, and especially the interaction between the pursuer and the flock. The herding algorithm is also demonstrated using numerical simulations.
KW - Aerial robotics
KW - biologically inspired robots
KW - field robots
KW - motion control
UR - http://www.scopus.com/inward/record.url?scp=85051036958&partnerID=8YFLogxK
U2 - 10.1109/TRO.2018.2853610
DO - 10.1109/TRO.2018.2853610
M3 - Article
AN - SCOPUS:85051036958
SN - 1552-3098
VL - 34
SP - 901
EP - 915
JO - IEEE Transactions on Robotics
JF - IEEE Transactions on Robotics
IS - 4
ER -