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Learning a single universal policy that can perform a diverse set of manipulation tasks is a promising new direction in robotics.
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kpam: Keypoint affordances for category-level robotic manipulation
Lucas Manuelli, Wei Gao, Peter Florence, and Russ Tedrake · 2019
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Affordances in robotic tasks–a survey
Paola Ardón, Èric Pairet, Katrin S Lohan, Subramanian Ramamoorthy, and Ronald Petrick · 2020
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Language models are few-shot learners
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An image is worth 16x16 words: Transformers for image recognition at scale
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Rlbench: The robot learning benchmark & learning environment
Stephen James, Zicong Ma, David Rovick Arrojo, and Andrew J Davison · 2020
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Clare Lyle, Mark van der Wilk, Marta Kwiatkowska, Yarin Gal, and Benjamin Bloem-Reddy · 2020
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Elise Van der Pol, Daniel Worrall, Herke van Hoof, Frans Oliehoek, and Max Welling · 2020
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Sim-to-real transfer in deep reinforcement learning for robotics: a survey
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Geometric and physical quantities improve e (3) equivariant message passing
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Transformers for one-shot visual imitation
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kpam-sc: Generalizable manipulation planning using keypoint affordance and shape completion
Wei Gao and Russ Tedrake · 2021
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A comprehensive survey on point cloud registration
Xiaoshui Huang, Guofeng Mei, Jian Zhang, and Rana Abbas · 2021
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Prompting decision transformer for few-shot policy generalization
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A survey on deep transfer learning and beyond
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One-shot imitation learning via interaction warping
Ondrej Biza, Skye Thompson, Kishore Reddy Pagidi, Abhinav Kumar, Elise van der Pol, Robin Walters, Thomas Kipf, Jan-Willem van de Meent, Lawson LS Wong, and Robert Platt · 2023
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Pointcept: A codebase for point cloud perception research
Pointcept Contributors · 2023
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Where2act: From pixels to actions for articulated 3d objects
Kaichun Mo, Leonidas J Guibas, Mustafa Mukadam, Abhinav Gupta, and Shubham Tulsiani · 2021
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Transporter networks: Rearranging the visual world for robotic manipulation
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Q-attention: Enabling efficient learning for vision-based robotic manipulation
Stephen James and Andrew J Davison · 2022
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Lepard: Learning partial point cloud matching in rigid and deformable scenes
Yang Li and Tatsuya Harada · 2022
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Act3d: 3d feature field transformers for multi-task robotic manipulation
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Rvt: Robotic view transformer for 3d object manipulation
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Learning dense visual descriptors using image augmentations for robot manipulation tasks
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Instruction-driven history-aware policies for robotic manipulations
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Learning category-level manipulation tasks from point clouds with dynamic graph cnns
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Structured world models from human videos
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Perceiver-actor: A multi-task transformer for robotic manipulation
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Chaineddiffuser: Unifying trajectory diffusion and keypose prediction for robotic manipulation
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Hyper-decision transformer for efficient online policy adaptation
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Optical flow boosts unsupervised localization and segmentation
Xinyu Zhang and Abdeslam Boularias · 2023
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Detect every thing with few examples, 2023
Xinyu Zhang, Yuting Wang, and Abdeslam Boularias · 2023
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