Pith. sign in

REVIEW 2 cited by

Edge Grasp Network: A Graph-Based SE(3)-invariant Approach to Grasp Detection

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2211.00191 v1 pith:ZAZHOV7Y submitted 2022-10-31 cs.RO cs.AIcs.CVcs.LG

Haojie Huang , Dian Wang , Xupeng Zhu , Robin Walters , Robert Platt This is my paper
classification cs.ROcs.AIcs.CVcs.LG
keywords grasppointclouddetectioninputmethodnetworkproblem
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Given point cloud input, the problem of 6-DoF grasp pose detection is to identify a set of hand poses in SE(3) from which an object can be successfully grasped. This important problem has many practical applications. Here we propose a novel method and neural network model that enables better grasp success rates relative to what is available in the literature. The method takes standard point cloud data as input and works well with single-view point clouds observed from arbitrary viewing directions.

Discussion (0). Sign in to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Action Map Policy: Learning 3D Closed-loop Manipulation via Pixel Classification

    cs.RO 2026-07 conditional novelty 6.0 of 10

    Projecting 3D gripper keypoints onto camera pixels and classifying those pixels yields millimeter-precise, multi-modal closed-loop manipulation faster than diffusion policies.

  2. SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space

    cs.RO 2025-07 conditional novelty 6.0 of 10

    Continuous SE(3) equivariance is embedded in the policy by representing states, actions, and denoising steps in spherical Fourier space, improving generalization to novel 3D arrangements.

Pith tools