Is Image-based Object Pose Estimation Ready to Support Grasping?

Fuente: arXiv
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Main Authors: Joyce, Eric C., Zhao, Qianwen, Burgdorfer, Nathaniel, Wang, Long, Mordohai, Philippos
Format: Preprint
Published: 2025
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author Joyce, Eric C.
Zhao, Qianwen
Burgdorfer, Nathaniel
Wang, Long
Mordohai, Philippos
author_facet Joyce, Eric C.
Zhao, Qianwen
Burgdorfer, Nathaniel
Wang, Long
Mordohai, Philippos
contents We present a framework for evaluating 6-DoF instance-level object pose estimators, focusing on those that require a single RGB (not RGB-D) image as input. Besides gaining intuition about how accurate these estimators are, we are interested in the degree to which they can serve as the sole perception mechanism for robotic grasping. To assess this, we perform grasping trials in a physics-based simulator, using image-based pose estimates to guide a parallel gripper and an underactuated robotic hand in picking up 3D models of objects. Our experiments on a subset of the BOP (Benchmark for 6D Object Pose Estimation) dataset compare five open-source object pose estimators and provide insights that were missing from the literature.
format Preprint
id arxiv_https___arxiv_org_abs_2512_01856
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Is Image-based Object Pose Estimation Ready to Support Grasping?
Joyce, Eric C.
Zhao, Qianwen
Burgdorfer, Nathaniel
Wang, Long
Mordohai, Philippos
Robotics
We present a framework for evaluating 6-DoF instance-level object pose estimators, focusing on those that require a single RGB (not RGB-D) image as input. Besides gaining intuition about how accurate these estimators are, we are interested in the degree to which they can serve as the sole perception mechanism for robotic grasping. To assess this, we perform grasping trials in a physics-based simulator, using image-based pose estimates to guide a parallel gripper and an underactuated robotic hand in picking up 3D models of objects. Our experiments on a subset of the BOP (Benchmark for 6D Object Pose Estimation) dataset compare five open-source object pose estimators and provide insights that were missing from the literature.
title Is Image-based Object Pose Estimation Ready to Support Grasping?
topic Robotics
url https://arxiv.org/abs/2512.01856