mlsanityData to 14 Oct 2026

Multi-level Reasoning for Robotic Assembly: From Sequence Inference to Contact Selection

arXiv 2312.10571 ↗First posted 17 Dec 2023cs.RO cs.AI cs.CVcited by 6

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Abstract (arXiv)

Automating the assembly of objects from their parts is a complex problem with innumerable applications in manufacturing, maintenance, and recycling. Unlike existing research, which is limited to target segmentation, pose regression, or using fixed target blueprints, our work presents a holistic multi-level framework for part assembly planning consisting of part assembly sequence inference, part motion planning, and robot contact optimization. We present the Part Assembly Sequence Transformer (PAST) -- a sequence-to-sequence neural network -- to infer assembly sequences recursively from a target blueprint. We then use a motion planner and optimization to generate part movements and contacts. To train PAST, we introduce D4PAS: a large-scale Dataset for Part Assembly Sequences (D4PAS) consisting of physically valid sequences for industrial objects. Experimental results show that our approach generalizes better than prior methods while needing significantly less computational time for inference.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 30 of its 41 references that are in the map. First posted on arXiv 17 Dec 2023.

Builds on

30 of 41 references.

References · 30

  1. 2017Attention Is All You Needcited by 60,361
  2. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  3. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
  4. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,838
  5. 2018Dynamic Graph CNN for Learning on Point Cloudscited by 2,223
  6. 2018Relational inductive biases, deep learning, and graph networkscited by 1,360
  7. 2021Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learningcited by 998
  8. 2021CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classificationcited by 806
  9. 2016CVXPY: A Python-Embedded Modeling Language for Convex Optimizationcited by 641
  10. 2018Residual Reinforcement Learning for Robot Controlcited by 274
  11. 2023FurnitureBench: Reproducible Real-World Benchmark for Long-Horizon Complex Manipulationcited by 133
  12. 2021JoinABLe: Learning Bottom-up Assembly of Parametric CAD Jointscited by 78
18 more
  1. 2020Generative 3D Part Assembly via Dynamic Graph Learningcited by 67
  2. 2022Factory: Fast Contact for Robotic Assemblycited by 54
  3. 2020Learning 3D Part Assembly from a Single Imagecited by 52
  4. 2021Tactile-RL for Insertion: Generalization to Objects of Unknown Geometrycited by 48
  5. 2022Neural Shape Mating: Self-Supervised Object Assembly with Adversarial Shape Priorscited by 43
  6. 2021Offline Meta-Reinforcement Learning for Industrial Insertioncited by 39
  7. 2022Learning Dexterous Manipulation from Exemplar Object Trajectories and Pre-Graspscited by 29
  8. 2022Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learningcited by 22
  9. 2018Learning Robotic Assembly from CADcited by 21
  10. 2021Learning Insertion Primitives with Discrete-Continuous Hybrid Action Space for Robotic Assembly Taskscited by 20
  11. 2021RoboAssembly: Learning Generalizable Furniture Assembly Policy in a Novel Multi-robot Contact-rich Simulation Environmentcited by 14
  12. 20216-DoF Contrastive Grasp Proposal Networkcited by 12
  13. 2023Rearrangement Planning for General Part Assemblycited by 12
  14. 2022Planning Assembly Sequence with Graph Transformercited by 10
  15. 2021Contact Pose Identification for Peg-in-Hole Assembly under Uncertaintiescited by 4
  16. 2021Learn to Grasp with Less Supervision: A Data-Efficient Maximum Likelihood Grasp Sampling Losscited by 4
  17. 2022Allowing Safe Contact in Robotic Goal-Reaching: Planning and Tracking in Operational and Null Spacescited by 3
  18. 2019Optimization Model for Planning Precision Grasps with Multi-Fingered Handscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 1; 2026: 2.

6 papers.

  1. 2024Manual-PA: Learning 3D Part Assembly from Instruction Diagramscited by 7
  2. 2025Text to Robotic Assembly of Multi Component Objects using 3D Generative AI and Vision Language Modelscited by 2
  3. 2026AssemblyBench: Physics-Aware Assembly of Complex Industrial Objectscited by 2
  4. 2024Subassembly to Full Assembly: Effective Assembly Sequence Planning through Graph-based Reinforcement Learningcited by 0
  5. 2024Learning Generalizable 3D Manipulation With 10 Demonstrationscited by 0
  6. 2026PVRA: A Pointwise Key-point Voting Framework for Robotic Assemblycited by 0