mlsanityData to 14 Oct 2026

6D Robotic Assembly Based on RGB-only Object Pose Estimation

arXiv 2208.12986 ↗First posted 27 Aug 2022cs.RO cs.CVcited by 9

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Abstract (arXiv)

Vision-based robotic assembly is a crucial yet challenging task as the interaction with multiple objects requires high levels of precision. In this paper, we propose an integrated 6D robotic system to perceive, grasp, manipulate and assemble blocks with tight tolerances. Aiming to provide an off-the-shelf RGB-only solution, our system is built upon a monocular 6D object pose estimation network trained solely with synthetic images leveraging physically-based rendering. Subsequently, pose-guided 6D transformation along with collision-free assembly is proposed to construct any designed structure with arbitrary initial poses. Our novel 3-axis calibration operation further enhances the precision and robustness by disentangling 6D pose estimation and robotic assembly. Both quantitative and qualitative results demonstrate the effectiveness of our proposed 6D robotic assembly system.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 26 of its 39 references that are in the map. First posted on arXiv 27 Aug 2022.

Builds on

26 of 39 references.

References · 26

  1. 2020YOLOv4: Optimal Speed and Accuracy of Object Detectioncited by 1,630
  2. 2018On the Continuity of Rotation Representations in Neural Networkscited by 1,214
  3. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 775
  4. 2018PVNet: Pixel-wise Voting Network for 6DoF Pose Estimationcited by 385
  5. 2020CosyPose: Consistent multi-view multi-object 6D pose estimationcited by 287
  6. 2018DeepIM: Deep Iterative Matching for 6D Pose Estimationcited by 283
  7. 2017SSD-6D: Making RGB-based 3D detection and 6D pose estimation great againcited by 243
  8. 2017BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depthcited by 225
  9. 2017Real-Time Seamless Single Shot 6D Object Pose Predictioncited by 210
  10. 2020BOP Challenge 2020 on 6D Object Localizationcited by 193
  11. 2019DPOD: 6D Pose Object Detector and Refinercited by 189
  12. 2019Implicit 3D Orientation Learning for 6D Object Detection from RGB Imagescited by 170
14 more
  1. 2020EPOS: Estimating 6D Pose of Objects with Symmetriescited by 148
  2. 2021GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimatorcited by 148
  3. 2018Reinforcement and Imitation Learning for Diverse Visuomotor Skillscited by 126
  4. 2018Segmentation-driven 6D Object Pose Estimationcited by 104
  5. 2020se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domainscited by 90
  6. 2019Single-Stage 6D Object Pose Estimationcited by 88
  7. 2021Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapescited by 71
  8. 2018Explaining the Ambiguity of Object Detection and 6D Pose From Visual Datacited by 68
  9. 2016Towards MRI-Based Autonomous Robotic US Acquisitions: A First Feasibility Studycited by 29
  10. 2021Vision-driven Compliant Manipulation for Reliable, High-Precision Assembly Taskscited by 18
  11. 2018Learning Pose Estimation for High-Precision Robotic Assembly Using Simulated Depth Imagescited by 11
  12. 2019Quickly Inserting Pegs into Uncertain Holes using Multi-view Images and Deep Network Trained on Synthetic Datacited by 6
  13. 2019Robots Assembling Machines: Learning from the World Robot Summit 2018 Assembly Challengecited by 6
  14. 2019Virtual Training for a Real Application: Accurate Object-Robot Relative Localization without Calibrationcited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 4; 2026: 3.

9 papers.

  1. 2024Deep Learning-Based Object Pose Estimation: A Comprehensive Surveycited by 40
  2. 2025Scalable Unseen Objects 6-DoF Absolute Pose Estimation with Robotic Integrationcited by 11
  3. 2025GIVEPose: Gradual Intra-class Variation Elimination for RGB-based Category-Level Object Pose Estimationcited by 6
  4. 2025MonoDiff9D: Monocular Category-Level 9D Object Pose Estimation via Diffusion Modelcited by 5
  5. 2025You Only Pose Once: A Minimalist's Detection Transformer for Monocular RGB Category-level 9D Multi-Object Pose Estimationcited by 3
  6. 2024A Collision-Aware Cable Grasping Method in Cluttered Environmentcited by 2
  7. 2026COG: Confidence-aware Optimal Geometric Correspondence for Unsupervised Single-reference Novel Object Pose Estimationcited by 1
  8. 2026Generalizable Robotic Insertion with World Modelscited by 0
  9. 2026SchemaPose: RGB-Based Category-Level Pose Estimation with Parametric Category Schemacited by 0