mlsanityData to 14 Oct 2026

Good Grasps Only: A data engine for self-supervised fine-tuning of pose estimation using grasp poses for verification

arXiv 2409.11512 ↗First posted 17 Sep 2024cs.RO cs.CVcited by 2

Not on the map. Why?

Abstract (arXiv)

In this paper, we present a novel method for self-supervised fine-tuning of pose estimation. Leveraging zero-shot pose estimation, our approach enables the robot to automatically obtain training data without manual labeling. After pose estimation the object is grasped, and in-hand pose estimation is used for data validation. Our pipeline allows the system to fine-tune while the process is running, removing the need for a learning phase. The motivation behind our work lies in the need for rapid setup of pose estimation solutions. Specifically, we address the challenging task of bin picking, which plays a pivotal role in flexible robotic setups. Our method is implemented on a robotics work-cell, and tested with four different objects. For all objects, our method increases the performance and outperforms a state-of-the-art method trained on the CAD model of the objects. Project page available at gogoengine.github.io

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 18 of its 36 references that are in the map. First posted on arXiv 17 Sep 2024.

Builds on

18 of 36 references.

References · 18

  1. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  2. 2018Dynamic Graph CNN for Learning on Point Cloudscited by 2,223
  3. 2018BOP: Benchmark for 6D Object Pose Estimationcited by 254
  4. 2021Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasetscited by 250
  5. 2020BOP Challenge 2020 on 6D Object Localizationcited by 193
  6. 2019Self-supervised 6D Object Pose Estimation for Robot Manipulationcited by 101
  7. 2020Self6D: Self-Supervised Monocular 6D Object Pose Estimationcited by 79
  8. 2024BOP Challenge 2023 on Detection, Segmentation and Pose Estimation of Seen and Unseen Rigid Objectscited by 60
  9. 2022Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimationcited by 34
  10. 2020Self-supervised Learning for Precise Pick-and-place without Object Modelcited by 21
  11. 2017A Self-supervised Learning System for Object Detection using Physics Simulation and Multi-view Pose Estimationcited by 11
  12. 2019Suction Grasp Region Prediction using Self-supervised Learning for Object Picking in Dense Cluttercited by 10
6 more
  1. 2023KeyMatchNet: Zero-Shot Pose Estimation in 3D Point Clouds by Generalized Keypoint Matchingcited by 7
  2. 2019Improving Data Efficiency of Self-supervised Learning for Robotic Graspingcited by 6
  3. 2022ParaPose: Parameter and Domain Randomization Optimization for Pose Estimation using Synthetic Datacited by 5
  4. 2022In-Hand Pose Estimation and Pin Inspection for Insertion of Through-Hole Componentscited by 3
  5. 2023Off-the-shelf bin picking workcell with visual pose estimation: A case study on the world robot summit 2018 kitting taskcited by 3
  6. 2020Online Self-Supervised Learning for Object Picking: Detecting Optimum Grasping Position using a Metric Learning Approachcited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Object Pose Distribution Estimation for Determining Revolution and Reflection Uncertainty in Point Cloudscited by 1
  2. 2026Towards a Modular Bin-picking Framework for Handling Object Pose Uncertaintiescited by 0