Proxemic group behaviors using reciprocal multi-agent navigation

Liang He; Jia Pan; Wenping Wang; Dinesh Manocha

doi:10.1109/ICRA.2016.7487147

Proxemic group behaviors using reciprocal multi-agent navigation

Liang He
, Jia Pan
, Wenping Wang
, Dinesh Manocha

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

28 Citations (Scopus)

Abstract

We present a decentralized algorithm for group-based coherent and reciprocal multi-agent navigation. In addition to generating collision-free trajectories for each agent, our approach is able to simulate macroscopic group movements and proxemic behaviors that result in coherent navigation. Our approach is general, makes no assumptions about the size or shape of the group, and can generate smooth trajectories for the agents. Furthermore, it can dynamically adapt to obstacles or the behavior of other agents. The additional overhead of generating proxemic group behaviors is relatively small and our approach can simulate hundreds of agents in real-time. We highlight its benefits on different benchmarks.

Original language	English
Title of host publication	Proceedings - IEEE International Conference on Robotics and Automation
Publisher	IEEE
Pages	292-297
Volume	2016-June
ISBN (Print)	9781467380263
DOIs	https://doi.org/10.1109/ICRA.2016.7487147
Publication status	Published - 8 Jun 2016
Externally published	Yes
Event	2016 IEEE International Conference on Robotics and Automation, ICRA 2016 - Stockholm, Sweden Duration: 16 May 2016 → 21 May 2016 https://www.icra2016.org/

Publication series

Name
Volume	2016-June
ISSN (Print)	1050-4729

Conference

Conference	2016 IEEE International Conference on Robotics and Automation, ICRA 2016
Place	Sweden
City	Stockholm
Period	16/05/16 → 21/05/16
Internet address	https://www.icra2016.org/

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10.1109/ICRA.2016.7487147

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title = "Proxemic group behaviors using reciprocal multi-agent navigation",

abstract = "We present a decentralized algorithm for group-based coherent and reciprocal multi-agent navigation. In addition to generating collision-free trajectories for each agent, our approach is able to simulate macroscopic group movements and proxemic behaviors that result in coherent navigation. Our approach is general, makes no assumptions about the size or shape of the group, and can generate smooth trajectories for the agents. Furthermore, it can dynamically adapt to obstacles or the behavior of other agents. The additional overhead of generating proxemic group behaviors is relatively small and our approach can simulate hundreds of agents in real-time. We highlight its benefits on different benchmarks.",

author = "Liang He and Jia Pan and Wenping Wang and Dinesh Manocha",

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booktitle = "Proceedings - IEEE International Conference on Robotics and Automation",

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He, L, Pan, J, Wang, W & Manocha, D 2016, Proxemic group behaviors using reciprocal multi-agent navigation. in Proceedings - IEEE International Conference on Robotics and Automation. vol. 2016-June, 7487147, IEEE, pp. 292-297, 2016 IEEE International Conference on Robotics and Automation, ICRA 2016, Stockholm, Sweden, 16/05/16. https://doi.org/10.1109/ICRA.2016.7487147

Proxemic group behaviors using reciprocal multi-agent navigation. / He, Liang; Pan, Jia; Wang, Wenping et al.
Proceedings - IEEE International Conference on Robotics and Automation. Vol. 2016-June IEEE, 2016. p. 292-297 7487147.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Proxemic group behaviors using reciprocal multi-agent navigation

AU - He, Liang

AU - Pan, Jia

AU - Wang, Wenping

AU - Manocha, Dinesh

PY - 2016/6/8

Y1 - 2016/6/8

N2 - We present a decentralized algorithm for group-based coherent and reciprocal multi-agent navigation. In addition to generating collision-free trajectories for each agent, our approach is able to simulate macroscopic group movements and proxemic behaviors that result in coherent navigation. Our approach is general, makes no assumptions about the size or shape of the group, and can generate smooth trajectories for the agents. Furthermore, it can dynamically adapt to obstacles or the behavior of other agents. The additional overhead of generating proxemic group behaviors is relatively small and our approach can simulate hundreds of agents in real-time. We highlight its benefits on different benchmarks.

AB - We present a decentralized algorithm for group-based coherent and reciprocal multi-agent navigation. In addition to generating collision-free trajectories for each agent, our approach is able to simulate macroscopic group movements and proxemic behaviors that result in coherent navigation. Our approach is general, makes no assumptions about the size or shape of the group, and can generate smooth trajectories for the agents. Furthermore, it can dynamically adapt to obstacles or the behavior of other agents. The additional overhead of generating proxemic group behaviors is relatively small and our approach can simulate hundreds of agents in real-time. We highlight its benefits on different benchmarks.

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DO - 10.1109/ICRA.2016.7487147

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781467380263

VL - 2016-June

SP - 292

EP - 297

BT - Proceedings - IEEE International Conference on Robotics and Automation

PB - IEEE

T2 - 2016 IEEE International Conference on Robotics and Automation, ICRA 2016

Y2 - 16 May 2016 through 21 May 2016

ER -

Proxemic group behaviors using reciprocal multi-agent navigation

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