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Diffusion models have recently been successfully applied to a wide range of robotics applications for learning complex multi-modal behaviors from data.
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Suboptimal variants of the conflict-based search algorithm for the multi-agent pathfinding problem
Max Barer, Guni Sharon, Roni Stern, and Ariel Felner · 2014
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Conflict-based search for optimal multi-agent pathfinding
Guni Sharon, Roni Stern, Ariel Felner, and Nathan R Sturtevant · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Learning structured output representation using deep conditional generative models
Kihyuk Sohn, Honglak Lee, and Xinchen Yan · 2015
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Improved solvers for bounded-suboptimal multi-agent path finding
Liron Cohen, Tansel Uras, TK Satish Kumar, Hong Xu, Nora Ayanian, and Sven Koenig · 2016
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Finding a needle in an exponential haystack: Discrete rrt for exploration of implicit roadmaps in multi-robot motion planning
Kiril Solovey, Oren Salzman, and Dan Halperin · 2016
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Data-driven planning via imitation learning
Sanjiban Choudhury, Mohak Bhardwaj, Sankalp Arora, Ashish Kapoor, Gireeja Ranade, Sebastian Scherer, and Debadeepta Dey · 2018
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Trajectory planning for quadrotor swarms
Wolfgang Hönig, James A Preiss, TK Satish Kumar, Gaurav S Sukhatme, and Nora Ayanian · 2018
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Multi-agent path finding for large agents
Jiaoyang Li, Pavel Surynek, Ariel Felner, Hang Ma, TK Satish Kumar, and Sven Koenig · 2019
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Priority inheritance with backtracking for iterative multi-agent path finding
Repaint: Inpainting using denoising diffusion probabilistic models, 2022
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, and Luc Van Gool · 2022
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Distributing collaborative multi-robot planning with gaussian belief propagation
Aalok Patwardhan, Riku Murai, and Andrew J. Davison · 2022
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Motion planning and control for mobile robot navigation using machine learning: a survey
Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone · 2022
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Is conditional generative modeling all you need for decision making?
Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, and Pulkit Agrawal · 2023
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Motion planning diffusion: Learning and planning of robot motions with diffusion models
Joao Carvalho, An T Le, Mark Baierl, Dorothea Koert, and Jan Peters · 2023
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Keisuke Okumura, Manao Machida, Xavier Défago, and Yasumasa Tamura · 2019
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Multi-agent pathfinding: Definitions, variants, and benchmarks
Roni Stern, Nathan Sturtevant, Ariel Felner, Sven Koenig, Hang Ma, Thayne Walker, Jiaoyang Li, Dor Atzmon, Liron Cohen, TK Kumar, et al · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Motion planning networks: Bridging the gap between learning-based and classical motion planners
Ahmed Hussain Qureshi, Yinglong Miao, Anthony Simeonov, and Michael C Yip · 2020
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Eecbs: A bounded-suboptimal search for multi-agent path finding
Jiaoyang Li, Wheeler Ruml, and Sven Koenig · 2021
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Score-based generative modeling through stochastic differential equations
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Cmax++: Leveraging experience in planning and execution using inaccurate models
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Motiondiffuser: Controllable multi-agent motion prediction using diffusion
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Generative skill chaining: Long-horizon skill planning with diffusion models
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Diffusion policy: Visuomotor policy learning via action diffusion
Cheng Chi, Zhenjia Xu, Siyuan Feng, Eric Cousineau, Yilun Du, Benjamin Burchfiel, Russ Tedrake, and Shuran Song · 2024
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Conflict-based model predictive control for scalable multi-robot motion planning
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Diffusion model for planning: A systematic literature review
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Adaptive online replanning with diffusion models
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