TY - GEN
T1 - Clone Swarms
T2 - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
AU - Zhou, Siyu
AU - Phielipp, Mariano J.
AU - Sefair, Jorge A.
AU - Walker, Sara I.
AU - Amor, Heni Ben
N1 - Funding Information:
VI. ACKNOWLEDGEMENT This research was funded by a gift from the Intel Corporation. Partial funding was also provided by the Defense Advanced Research Projects Agency (DARPA) under Cooperative Agreement Number HR0011-18-2-0022. The content of the information does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred. Approved for public release; distribution is unlimited.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - In this paper, we propose SwarmNet - a neural network architecture that can learn to predict and imitate the behavior of an observed swarm of agents in a centralized manner. Tested on artificially generated swarm motion data, the network achieves high levels of prediction accuracy and imitation authenticity. We compare our model to previous approaches for modelling interaction systems and show how modifying components of other models gradually approaches the performance of ours. Finally, we also discuss an extension of SwarmNet that can deal with nondeterministic, noisy, and uncertain environments, as often found in robotics applications.
AB - In this paper, we propose SwarmNet - a neural network architecture that can learn to predict and imitate the behavior of an observed swarm of agents in a centralized manner. Tested on artificially generated swarm motion data, the network achieves high levels of prediction accuracy and imitation authenticity. We compare our model to previous approaches for modelling interaction systems and show how modifying components of other models gradually approaches the performance of ours. Finally, we also discuss an extension of SwarmNet that can deal with nondeterministic, noisy, and uncertain environments, as often found in robotics applications.
UR - http://www.scopus.com/inward/record.url?scp=85081157511&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081157511&partnerID=8YFLogxK
U2 - 10.1109/IROS40897.2019.8967824
DO - 10.1109/IROS40897.2019.8967824
M3 - Conference contribution
AN - SCOPUS:85081157511
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 4092
EP - 4099
BT - 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 3 November 2019 through 8 November 2019
ER -