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Recent advances in diffusion models hold significant potential in robotics, enabling the generation of diverse and smooth trajectories directly from raw representations of the environment.
Probabilistic roadmaps for path planning in high-dimensional configuration spaces
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Rapidly-exploring random trees: A new tool for path planning
LaValle, S · 1998
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Planning algorithms
LaValle, S. M · 2006
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Chomp: Gradient optimization techniques for efficient motion planning
Ratliff, N., Zucker, M., Bagnell, J. A., and Srinivasa, S · 2009
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Distributed optimization and statistical learning via the alternating direction method of multipliers
Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J., et al · 2011
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Bayesian learning via stochastic gradient langevin dynamics
Welling, M. and Teh, Y. W · 2011
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Generation of collision-free trajectories for a quadrocopter fleet: A sequential convex programming approach
Augugliaro, F., Schoellig, A. P., and D’Andrea, R · 2012
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Decoupled multiagent path planning via incremental sequential convex programming
Chen, Y., Cutler, M., and How, J. P · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Sohl-Dickstein, J., Weiss, E., Maheswaranathan, N., and Ganguli, S · 2015
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Learning sampling distributions for robot motion planning
Ichter, B., Harrison, J., and Pavone, M · 2018
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Global convergence of langevin dynamics based algorithms for nonconvex optimization
Xu, P., Chen, J., Zou, D., and Gu, Q · 2018
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Improved heuristics for multi-agent path finding with conflict-based search
Li, J., Felner, A., Boyarski, E., Ma, H., and Koenig, S · 2019
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Generative modeling by estimating gradients of the data distribution
Song, Y. and Ermon, S · 2019
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Multi-agent pathfinding: Definitions, variants, and benchmarks
Stern, R., Sturtevant, N., Felner, A., Koenig, S., Ma, H., Walker, T., Li, J., Atzmon, D., Cohen, L., Kumar, T., et al · 2019
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Denoising diffusion probabilistic models
Ho, J., Jain, A., and Abbeel, P · 2020
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Deep learning can accelerate grasp-optimized motion planning
Ichnowski, J., Avigal, Y., Satish, V., and Goldberg, K · 2020
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Score-based generative modeling through stochastic differential equations
Motion planning diffusion: Learning and planning of robot motions with diffusion models
Carvalho, J., Le, A. T., Baierl, M., Koert, D., and Peters, J · 2023
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Motion planning for autonomous driving: The state of the art and future perspectives
Teng, S., Hu, X., Deng, P., Li, B., Li, Y., Ai, Y., Yang, D., Li, L., Xuanyuan, Z., Zhu, F., and Chen, L · 2023
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Motion planning diffusion: Learning and adapting robot motion planning with diffusion models
Carvalho, J., Le, A., Kicki, P., Koert, D., and Peters, J · 2024
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Constrained synthesis with projected diffusion models
Christopher, J. K., Baek, S., and Fioretto, F · 2024
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Learning constrained optimization with deep augmented lagrangian methods
Kotary, J. and Fioretto, F · 2024
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Song, Y., Sohl-Dickstein, J., Kingma, D. P., Kumar, A., Ermon, S., and Poole, B · 2020
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Eecbs: A bounded-suboptimal search for multi-agent path finding
Li, J., Ruml, W., and Koenig, S · 2021
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Improved denoising diffusion probabilistic models
Nichol, A. Q. and Dhariwal, P · 2021
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A survey of learning-based robot motion planning
Wang, J., Zhang, T., Ma, N., Li, Z., Ma, H., Meng, F., and Meng, M. Q.-H · 2021
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Planning with diffusion for flexible behavior synthesis
Janner, M., Du, Y., Tenenbaum, J. B., and Levine, S · 2022
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Fast approximations for job shop scheduling: A lagrangian dual deep learning method
Kotary, J., Fioretto, F., and Van Hentenryck, P · 2022
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Priority inheritance with backtracking for iterative multi-agent path finding
Okumura, K., Machida, M., Défago, X., and Tamura, Y
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Potential based diffusion motion planning
Luo, Y., Sun, C., Tenenbaum, J. B., and Du, Y · 2024
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Edmp: Ensemble-of-costs-guided diffusion for motion planning
Saha, K., Mandadi, V., Reddy, J., Srikanth, A., Agarwal, A., Sen, B., Singh, A., and Krishna, M · 2024
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Diffusion model for planning: A systematic literature review
Ubukata, T., Li, J., and Tei, K · 2024
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Constrained generative modeling with manually bridged diffusion models
Naderiparizi, S., Liang, X., Zwartsenberg, B., and Wood, F · 2025
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Multi-robot motion planning with diffusion models
Shaoul, Y., Mishani, I., Vats, S., Li, J., and Likhachev, M · 2025
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