RGB-Only Reconstruction of Tabletop Scenes for Collision-Free Manipulator Control
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Abstract (arXiv)
We present a system for collision-free control of a robot manipulator that uses only RGB views of the world. Perceptual input of a tabletop scene is provided by multiple images of an RGB camera (without depth) that is either handheld or mounted on the robot end effector. A NeRF-like process is used to reconstruct the 3D geometry of the scene, from which the Euclidean full signed distance function (ESDF) is computed. A model predictive control algorithm is then used to control the manipulator to reach a desired pose while avoiding obstacles in the ESDF. We show results on a real dataset collected and annotated in our lab.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 39 of its 57 references that are in the map. First posted on arXiv 21 Oct 2022.
Builds on
39 of 57 references.
References · 39
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27 more
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Built on by
Citing papers per year: 2023: 4; 2024: 3; 2025: 3.
10 papers.
- 2023HANDAL: A Dataset of Real-World Manipulable Object Categories with Pose Annotations, Affordances, and Reconstructionscited by 47
- 2023D3Fields: Dynamic 3D Descriptor Fields for Zero-Shot Generalizable Rearrangementcited by 35
- 2024NeRFs in Robotics: A Surveycited by 16
- 2025IAAO: Interactive Affordance Learning for Articulated Objects in 3D Environmentscited by 11
- 2023HandNeRF: Learning to Reconstruct Hand-Object Interaction Scene from a Single RGB Imagecited by 10
- 2023BAA-NGP: Bundle-Adjusting Accelerated Neural Graphics Primitivescited by 8
- 2025RaySt3R: Predicting Novel Depth Maps for Zero-Shot Object Completioncited by 5
- 2025TabletopGen: Tabletop Scene Generation and Interactive Simulation for Robotic Manipulationcited by 2
- 2024NeRFDeformer: NeRF Transformation from a Single View via 3D Scene Flowscited by 1
- 2024GUMBEL-NERF: Representing Unseen Objects as Part-Compositional Neural Radiance Fieldscited by 0
- 2025TabletopGen: Tabletop Scene Generation and Interactive Simulation for Robotic Manipulation1 Dec 2025
- 2025RaySt3R: Predicting Novel Depth Maps for Zero-Shot Object Completion5 Jun 2025
- 2025IAAO: Interactive Affordance Learning for Articulated Objects in 3D Environments9 Apr 2025
- 2024GUMBEL-NERF: Representing Unseen Objects as Part-Compositional Neural Radiance Fields27 Oct 2024
- 2024NeRFDeformer: NeRF Transformation from a Single View via 3D Scene Flows15 Jun 2024
- 2024NeRFs in Robotics: A Survey2 May 2024
- 2023D3Fields: Dynamic 3D Descriptor Fields for Zero-Shot Generalizable Rearrangement28 Sep 2023
- 2023HandNeRF: Learning to Reconstruct Hand-Object Interaction Scene from a Single RGB Image14 Sep 2023
- 2023HANDAL: A Dataset of Real-World Manipulable Object Categories with Pose Annotations, Affordances, and Reconstructions2 Aug 2023
- 2023BAA-NGP: Bundle-Adjusting Accelerated Neural Graphics Primitives7 Jun 2023