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Recent advances in diffusion models have opened new avenues for research into embodied AI agents and robotics.
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1923
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2021
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2021
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2021
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2021
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2022
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A. Fishman, A. Murali, C. Eppner, B. Peele, B. Boots, and D. Fox, “Motion policy networks,” in
2022
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Y. Ma, F. Farshidian, T. Miki, J. Lee, and M. Hutter, “Combining learning-based locomotion policy with model-based manipulation for legged mobile manipulators,”
2022
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2022
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2023
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T. J. Wang, J. Zheng, P. Ma, Y. Du, B. Kim, A. Spielberg, J. B. Tenenbaum, C. Gan, and D. Rus, “Diffusebot: Breeding soft robots with physics-augmented generative diffusion models,” in
2023
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2023
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2023
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J. Chiu, J. Sleiman, M. Mittal, F. Farshidian, and M. Hutter, “A collision-free MPC for whole-body dynamic locomotion and manipulation,” in
2022
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M. Han, Z. Zhang, Z. Jiao, X. Xie, Y. Zhu, S. Zhu, and H. Liu, “Scene reconstruction with functional objects for robot autonomy,”
2022
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R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer, “High-resolution image synthesis with latent diffusion models,” in
2022
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M. Shridhar, L. Manuelli, and D. Fox, “Perceiver-actor: A multi-task transformer for robotic manipulation,” in
2022
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M. Janner, Y. Du, J. B. Tenenbaum, and S. Levine, “Planning with diffusion for flexible behavior synthesis,” in
2022
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J. Urain, A. T. Le, A. Lambert, G. Chalvatzaki, B. Boots, and J. Peters, “Learning implicit priors for motion optimization,” in
2022
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M. Mittal, D. Hoeller, F. Farshidian, M. Hutter, and A. Garg, “Articulated object interaction in unknown scenes with whole-body mobile manipulation,” in
2022
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2023
Later among the works it cites.
T. Chen, “On the importance of noise scheduling for diffusion models,”
2023
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J. Song, Q. Zhang, H. Yin, M. Mardani, M. Liu, J. Kautz, Y. Chen, and A. Vahdat, “Loss-guided diffusion models for plug-and-play controllable generation,” in
2023
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2024
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M. Han, Y. Zhu, S.-C. Zhu, Y. N. Wu, and Y. Zhu, “Interpret: Interactive predicate learning from language feedback for generalizable task planning,” in
2024
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N. Yokoyama, A. Clegg, J. Truong, E. Undersander, T. Yang, S. Arnaud, S. Ha, D. Batra, and A. Rai, “ASC: adaptive skill coordination for robotic mobile manipulation,”
2024
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L. Naik, S. Kalkan, and N. Krüger, “Pre-grasp approaching on mobile robots: A pre-active layered approach,”
2024
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2024
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C. Liu, H. Wu, Y. Zhong, X. Zhang, Y. Wang, and W. Xie, “Intelligent grimm - open-ended visual storytelling via latent diffusion models,” in
2024
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Y. Ze, G. Zhang, K. Zhang, C. Hu, M. Wang, and H. Xu, “3d diffusion policy,”
2024
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G. Yan, Y.-H. Wu, and X. Wang, “Dnact: Diffusion guided multi-task 3d policy learning,”
2024
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X. Ma, S. Patidar, I. Haughton, and S. James, “Hierarchical diffusion policy for kinematics-aware multi-task robotic manipulation,” in
2024
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W. K. Kim, M. Yoo, and H. Woo, “Robust policy learning via offline skill diffusion,”
2024
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A. Sridhar, D. Shah, C. Glossop, and S. Levine, “Nomad: Goal masked diffusion policies for navigation and exploration,” in
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X. Xu, H. Ha, and S. Song, “Dynamics-guided diffusion model for robot manipulator design,”
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S. Noh, R. Kang, T. Kim, S. Back, S. Bak, and K. Lee, “Learning to place unseen objects stably using a large-scale simulation,”
2024
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Z. Zhang, S. Yan, M. Han, Z. Wang, X. Wang, S.-C. Zhu, and H. Liu, “M
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Y. Yang, B. Jia, P. Zhi, and S. Huang, “Physcene: Physically interactable 3d scene synthesis for embodied AI,” in
2024
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