mlsanityData to 14 Oct 2026

Assembly Planning from Observations under Physical Constraints

arXiv 2204.09616 ↗First posted 20 Apr 2022cs.RO cs.AI cs.CVcited by 1

Not on the map. Why?

Abstract (arXiv)

This paper addresses the problem of copying an unknown assembly of primitives with known shape and appearance using information extracted from a single photograph by an off-the-shelf procedure for object detection and pose estimation. The proposed algorithm uses a simple combination of physical stability constraints, convex optimization and Monte Carlo tree search to plan assemblies as sequences of pick-and-place operations represented by STRIPS operators. It is efficient and, most importantly, robust to the errors in object detection and pose estimation unavoidable in any real robotic system. The proposed approach is demonstrated with thorough experiments on a UR5 manipulator.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 18 of its 36 references that are in the map. First posted on arXiv 20 Apr 2022.

Builds on

18 of 36 references.

References · 18

  1. 2017Mask R-CNNcited by 7,277
  2. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 775
  3. 2016CVXPY: A Python-Embedded Modeling Language for Convex Optimizationcited by 641
  4. 2019DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusioncited by 355
  5. 2020CosyPose: Consistent multi-view multi-object 6D pose estimationcited by 287
  6. 2018DeepIM: Deep Iterative Matching for 6D Pose Estimationcited by 283
  7. 2018BOP: Benchmark for 6D Object Pose Estimationcited by 254
  8. 2017BB8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depthcited by 225
  9. 2017T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objectscited by 210
  10. 2019PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimationcited by 204
  11. 2017A Rewriting System for Convex Optimization Problemscited by 179
  12. 2018PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planningcited by 150
6 more
  1. 2020Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Imagecited by 48
  2. 2019Object-Centric Task and Motion Planning in Dynamic Environmentscited by 35
  3. 2019Monte-Carlo Tree Search for Efficient Visually Guided Rearrangement Planningcited by 24
  4. 2021Efficient and Interpretable Robot Manipulation with Graph Neural Networkscited by 22
  5. 2017Combining Neural Networks and Tree Search for Task and Motion Planning in Challenging Environmentscited by 19
  6. 2020Learning visual policies for building 3D shape categoriescited by 2

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Citing papers per year: 2024: 1.

1 paper.

  1. 2024Physics-Aware Combinatorial Assembly Sequence Planning using Data-free Action Maskingcited by 5