research-article

Deep Integration of Physical Humanoid Control and Crowd Navigation

Authors:

Brandon Haworth,

Seonghyeon Moon,

Petros Faloutsos,

Mubbasir KapadiaAuthors Info & Claims

MIG '20: Proceedings of the 13th ACM SIGGRAPH Conference on Motion, Interaction and Games

Article No.: 15, Pages 1 - 10

https://doi.org/10.1145/3424636.3426894

Published: 22 November 2020 Publication History

Abstract

Many multi-agent navigation approaches make use of simplified representations such as a disk. These simplifications allow for fast simulation of thousands of agents but limit the simulation accuracy and fidelity. In this paper, we propose a fully integrated physical character control and multi-agent navigation method. In place of sample complex online planning methods, we extend the use of recent deep reinforcement learning techniques. This extension improves on multi-agent navigation models and simulated humanoids by combining Multi-Agent and Hierarchical Reinforcement Learning. We train a single short term goal-conditioned low-level policy to provide directed walking behaviour. This task-agnostic controller can be shared by higher-level policies that perform longer-term planning. The proposed approach produces reciprocal collision avoidance, robust navigation, and emergent crowd behaviours. Furthermore, it offers several key affordances not previously possible in multi-agent navigation including tunable character morphology and physically accurate interactions with agents and the environment. Our results show that the proposed method outperforms prior methods across environments and tasks, as well as, performing well in terms of zero-shot generalization over different numbers of agents and computation time.

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cover image ACM Conferences

MIG '20: Proceedings of the 13th ACM SIGGRAPH Conference on Motion, Interaction and Games

October 2020

190 pages

ISBN:9781450381710

DOI:10.1145/3424636

Copyright © 2020 ACM.

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Published: 22 November 2020

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October 16 - 18, 2020

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Cited By

Shao WLin FXu RMeng FWang H(2024)UAV-Assisted NOMA Network Power Allocation Under Offshore Multi-energy Complementary Power Generation SystemProceedings of the 13th International Conference on Computer Engineering and Networks10.1007/978-981-99-9239-3_12(125-136)Online publication date: 4-Jan-2024
https://doi.org/10.1007/978-981-99-9239-3_12
Ye JLiu ZLiu TWu YWang Y(2024)Crowd evacuation simulation based on hierarchical agent model and physics‐based character controlComputer Animation and Virtual Worlds10.1002/cav.226335:3Online publication date: 27-May-2024
https://doi.org/10.1002/cav.2263
Younes MKijak EKulpa RMalinowski SMulton F(2023)MAAIPProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/36069266:3(1-20)Online publication date: 24-Aug-2023
https://doi.org/10.1145/3606926
Zhang YGopinath DYe YHodgins JTurk GWon J(2023)Simulation and Retargeting of Complex Multi-Character InteractionsACM SIGGRAPH 2023 Conference Proceedings10.1145/3588432.3591491(1-11)Online publication date: 23-Jul-2023
https://dl.acm.org/doi/10.1145/3588432.3591491
Hu KHaworth BBerseth GPavlovic VFaloutsos PKapadia M(2023)Heterogeneous Crowd Simulation Using Parametric Reinforcement LearningIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.313903129:4(2036-2052)Online publication date: 1-Apr-2023
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Ma YKhan QCremers D(2023)Multi Agent Navigation in Unconstrained Environments using a Centralized Attention based Graphical Neural Network Controller2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC57777.2023.10422072(2893-2900)Online publication date: 24-Sep-2023
https://doi.org/10.1109/ITSC57777.2023.10422072
Rempe DLuo ZPeng XYuan YKitani KKreis KFidler SLitany O(2023)Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52729.2023.01322(13756-13766)Online publication date: Jun-2023
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Lemonari MBlanco RCharalambous PPelechano NAvraamides MPettré JChrysanthou Y(2022)Authoring Virtual Crowds: A SurveyComputer Graphics Forum10.1111/cgf.1450641:2(677-701)Online publication date: 24-May-2022
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