Deep Reinforcement Learning for Fluid Dynamics and Control

Reinforcement learning based on deep learning is currently being used for impressive control of fluid dynamic systems. This video will describe recent advances, including for mimicking the behavior of birds and fish, for turbulence closure modeling with sub-grid-scale models, and for robotic flight demonstrations.

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Links to papers in video:

@3:58 Machine learning for fluid mechanics
Brunton, Noack, Koumoutsakos, Ann. Rev. Fluid Mech 52:477--508, 2020
https://www.annualreviews.org/doi/pdf/10.1146/annurev-fluid-010719-060214

@5:04 Efficient collective swimming by harnessing vortices through deep reinforcement learning
Verma, Novati, Koumoutsakos, Proc. Nat. Acad. Sci. 115(23):5849--5854, 2018
https://www.pnas.org/content/115/23/5849

@6:57 Automating turbulence modelling by multi-agent reinforcement learning
Novati, Lascombes de Laroussilhe, Koumoutsakos, Nat. Mach. Int. 3:87--96, 2021
https://www.nature.com/articles/s42256-020-00272-0
@8:47 A review of Deep Reinforcement Learning for fluid mechanics,
Garnier, Viquerat, Rabault, Larcher, Kuhnle, Hachem, 2019
https://arxiv.org/abs/1908.04127

@9:57 Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control
Rabault, Kuchta, Jensen, Reglade, Cerardi, J. Fluid Mech. 865, 2019
https://doi.org/10.1017/jfm.2019.62

@10:56 Reinforcement learning for bluff body active flow control in experiments and simulations
Fan, Yang, Wang, Triantafyllou, Karniadakis, Proc. Nat. Acad. Sci. 117(42), 2020
https://doi.org/10.1073/pnas.2004939117

@11:50 Fluid directed rigid body control using deep reinforcement learning
Ma, Tian, Pan, Ren, Manocha, SIGGRAPH 2018
https://gamma.cs.unc.edu/DRL_FluidRigid/

@13:26 Autonomous helicopter flight via Reinforcement Learning
Ng, Kim, Jordan, Sastry, NeurIPS 2004
https://papers.nips.cc/paper/2003/file/b427426b8acd2c2e53827970f2c2f526-Paper.pdf

@13:26 An Application of Reinforcement Learning to Aerobatic Helicopter Flight
Abbeel, Coates, Quigly, Ng, NeurIPS 2007
https://proceedings.neurips.cc/paper/2006/file/98c39996bf1543e974747a2549b3107c-Paper.pdf

@13:26 Autonomous helicopter aerobatics through apprenticeship learning
Abeel, Coates, Ng, Int J Rob Res 2010
https://journals.sagepub.com/doi/abs/10.1177/0278364910371999

@14:02 Learning to fly like a bird
Tedrake, Jackowski, Cory, Roberts, Hoburg, Int. Symp. Rob. Res. 2009
https://groups.csail.mit.edu/robotics-center/public_papers/Tedrake09.pdf

@14:58 Control of a Quadrotor with Reinforcement Learning
Hwangbo, Sa, Siegwart, Hutter, IEEE Rob Aut 2(4) 2017
https://arxiv.org/abs/1707.05110

@15:22 Learning to soar in turbulent environments
Reddy, Celani, Sejnowski, Vergassola Proc. Nat. Acad. Sci. 113(33, 2016
https://www.pnas.org/content/113/33/E4877

@16:31 Learning to Fly: Computational Controller Design for Hybrid UAVs with Reinforcement Learning
Xu, Du, Foshey, Li, Zhu, Schulz, Matusik, SIGGRAPH 2019
https://people.csail.mit.edu/jiex/papers/LearningToFly/index.html

Видео Deep Reinforcement Learning for Fluid Dynamics and Control канала Steve Brunton