AISPO proposes a depth completion method using multi-scale RGB-D fusion and an affine-invariant shape prior to improve depth reliability and manipulation success for non-Lambertian objects.
Dex-nerf:Usinga neuralradiancefieldtograsptransparentobjects
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A simulation-trained model predicts voxel occupancy from single RGB views for transparent object grasping and transfers to real robotic setups without fine-tuning.
A survey of 106 papers finds quality inspection dominates 3D reconstruction use in manufacturing at 40 percent of applications, with a shift toward hybrid sensor systems and a noted gap in unified frameworks.
citing papers explorer
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AISPO: Enhancing Depth Reliability for Robotic Manipulation of Non-Lambertian Objects via Affine-Invariant Shape Prior
AISPO proposes a depth completion method using multi-scale RGB-D fusion and an affine-invariant shape prior to improve depth reliability and manipulation success for non-Lambertian objects.
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Trans2Occ: Voxel Occupancy Estimation and Grasp for Transparent Objects from Simulation to Reality
A simulation-trained model predicts voxel occupancy from single RGB views for transparent object grasping and transfers to real robotic setups without fine-tuning.
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3D Reconstruction Techniques in the Manufacturing Domain: Applications, Research Opportunities and Use Cases
A survey of 106 papers finds quality inspection dominates 3D reconstruction use in manufacturing at 40 percent of applications, with a shift toward hybrid sensor systems and a noted gap in unified frameworks.