mlsanityData to 7 Oct 2026

Object-Centric Task and Motion Planning in Dynamic Environments

arXiv 1911.04679 ↗First posted 12 Nov 2019cs.RO cs.AIcited by 34

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Abstract (arXiv)

We address the problem of applying Task and Motion Planning (TAMP) in real world environments. TAMP combines symbolic and geometric reasoning to produce sequential manipulation plans, typically specified as joint-space trajectories, which are valid only as long as the environment is static and perception and control are highly accurate. In case of any changes in the environment, slow re-planning is required. We propose a TAMP algorithm that optimizes over Cartesian frames defined relative to target objects. The resulting plan then remains valid even if the objects are moving and can be executed by reactive controllers that adapt to these changes in real time. We apply our TAMP framework to a torque-controlled robot in a pick and place setting and demonstrate its ability to adapt to changing environments, inaccurate perception, and imprecise control, both in simulation and the real world.

Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Nov 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 4; 2023: 6; 2024: 12; 2025: 9; 2026: 1.

34 papers.

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  1. 2024ReKep: Spatio-Temporal Reasoning of Relational Keypoint Constraints for Robotic Manipulationcited by 305
  2. 2023RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulationcited by 206
  3. 2022VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priorscited by 135
  4. 2023Gen2Sim: Scaling up Robot Learning in Simulation with Generative Modelscited by 62
  5. 2023Learning Generalizable Manipulation Policies with Object-Centric 3D Representationscited by 60
  6. 2024Robot See Robot Do: Imitating Articulated Object Manipulation with Monocular 4D Reconstructioncited by 51
  7. 2024Vision-based Manipulation from Single Human Video with Open-World Object Graphscited by 46
  8. 2025ControlVLA: Few-shot Object-centric Adaptation for Pre-trained Vision-Language-Action Modelscited by 43
  9. 2023Energy-based Models are Zero-Shot Planners for Compositional Scene Rearrangementcited by 30
  10. 2025Rethinking Progression of Memory State in Robotic Manipulation: An Object-Centric Perspectivecited by 20
  11. 2024A Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approachescited by 19
  12. 2023Generalizable Long-Horizon Manipulations with Large Language Modelscited by 16
22 more
  1. 2024Object-Centric Instruction Augmentation for Robotic Manipulationcited by 16
  2. 2024Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Modelscited by 16
  3. 2024Language-Guided Object-Centric Diffusion Policy for Generalizable and Collision-Aware Robotic Manipulationcited by 14
  4. 2023Object-Centric Learning with Slot Mixture Modulecited by 11
  5. 2025Are We Done with Object-Centric Learning?cited by 10
  6. 2021Learning to Search in Task and Motion Planning with Streamscited by 9
  7. 2024Learning from 10 Demos: Generalisable and Sample-Efficient Policy Learning with Oriented Affordance Framescited by 9
  8. 2022GraspARL: Dynamic Grasping via Adversarial Reinforcement Learningcited by 6
  9. 2024Task and Motion Planning for Execution in the Realcited by 6
  10. 2024Closed Loop Interactive Embodied Reasoning for Robot Manipulationcited by 4
  11. 2021Generalizing Object-Centric Task-Axes Controllers using Keypointscited by 3
  12. 2022Active Task Randomization: Learning Robust Skills via Unsupervised Generation of Diverse and Feasible Taskscited by 3
  13. 2025Pick-and-place Manipulation Across Grippers Without Retraining: A Learning-optimization Diffusion Policy Approachcited by 3
  14. 2025Executable Analytic Concepts as the Missing Link Between VLM Insight and Precise Manipulationcited by 3
  15. 2024Symbolic Disentangled Representations for Imagescited by 2
  16. 2025Inference-stage Adaptation-projection Strategy Adapts Diffusion Policy to Cross-manipulators Scenarioscited by 2
  17. 2022Assembly Planning from Observations under Physical Constraintscited by 1
  18. 2024Logic Learning from Demonstrations for Multi-step Manipulation Tasks in Dynamic Environmentscited by 1
  19. 2025GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learningcited by 1
  20. 2025SAGE: Scene Graph-Aware Guidance and Execution for Long-Horizon Manipulation Taskscited by 0
  21. 2025GLUE: Global-Local Unified Encoding for Imitation Learning via Key-Patch Trackingcited by 0
  22. 2026Explicit Kinematic Guidance from Analytic Concepts for Vision-Language-Action Modelscited by 0