mlsanityData to 7 Oct 2026

Real-Time Operator Takeover for Visuomotor Diffusion Policy Training

arXiv 2502.02308 ↗First posted 4 Feb 2025cs.RO cs.LGcited by 5

On the map: Diffusion models → Diffusion and flow policies for robotics

Abstract (arXiv)

We present a Real-Time Operator Takeover (RTOT) paradigm that enables operators to seamlessly take control of a live visuomotor diffusion policy, guiding the system back to desirable states or providing targeted corrective demonstrations. Within this framework, the operator can intervene to correct the robot's motion, after which control is smoothly returned to the policy until further intervention is needed. We evaluate the takeover framework on three tasks spanning rigid, deformable, and granular objects, and show that incorporating targeted takeover demonstrations significantly improves policy performance compared with training on an equivalent number of initial demonstrations alone. Additionally, we provide an in-depth analysis of the Mahalanobis distance as a signal for automatically identifying undesirable or out-of-distribution states during execution. Supporting materials, including videos of the initial and takeover demonstrations and all experiments, are available on the project website: https://operator-takeover.github.io/

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 33 of its 48 references that are in the map. First posted on arXiv 4 Feb 2025.

Builds on

33 of 48 references.

Closest ancestors · 5

Same direction, newest first

  1. 2024A Robotic Skill Learning System Built Upon Diffusion Policies and Foundation Models25 Mar
  2. 2023NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration11 Oct
  3. 2023Goal-Conditioned Imitation Learning using Score-based Diffusion Policies5 Apr
  4. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusion7 Mar
  5. 2022DALL-E-Bot: Introducing Web-Scale Diffusion Models to Robotics5 Oct

Other references · 28

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2020Conservative Q-Learning for Offline Reinforcement Learningcited by 1,777
  3. 2021Generalized Out-of-Distribution Detection: A Surveycited by 796
  4. 2022Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulationcited by 545
  5. 2021Implicit Behavioral Cloningcited by 442
  6. 2024Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperationcited by 377
  7. 2022Behavior Transformers: Cloning k modes with one stonecited by 299
  8. 2018HG-DAgger: Interactive Imitation Learning with Human Expertscited by 245
  9. 2021The Surprising Effectiveness of Representation Learning for Visual Imitationcited by 149
  10. 2023AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation Systemcited by 136
  11. 2018EnsembleDAgger: A Bayesian Approach to Safe Imitation Learningcited by 96
  12. 2020Transformers for One-Shot Visual Imitationcited by 77
16 more
  1. 2023On the Generalization Properties of Diffusion Modelscited by 67
  2. 2023NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesiscited by 56
  3. 2023Movement Primitive Diffusion: Learning Gentle Robotic Manipulation of Deformable Objectscited by 40
  4. 2021On the Sample Complexity of Stability Constrained Imitation Learningcited by 38
  5. 2022A System-Level View on Out-of-Distribution Data in Roboticscited by 33
  6. 2023Teleoperation of Humanoid Robots: A Surveycited by 32
  7. 2024ACE: A Cross-Platform Visual-Exoskeletons System for Low-Cost Dexterous Teleoperationcited by 32
  8. 2024ARCap: Collecting High-quality Human Demonstrations for Robot Learning with Augmented Reality Feedbackcited by 31
  9. 2024Bimanual Dexterity for Complex Taskscited by 22
  10. 2022Back to the Manifold: Recovering from Out-of-Distribution Statescited by 19
  11. 2024Unfolding the Literature: A Review of Robotic Cloth Manipulationcited by 14
  12. 2023A Virtual Reality Framework for Human-Robot Collaboration in Cloth Foldingcited by 7
  13. 2021ARROCH: Augmented Reality for Robots Collaborating with a Humancited by 5
  14. 2024Puppeteer Your Robot: Augmented Reality Leader-Follower Teleoperationcited by 4
  15. 2022Shared-Control Robotic Manipulation in Virtual Realitycited by 3
  16. 2023Imitation Learning from Purified Demonstrationscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.

  1. 2026VLA-Corrector: Lightweight Detect-and-Correct Inference for Adaptive Action Horizoncited by 14
  2. 2026Preference Aligned Visuomotor Diffusion Policies for Deformable Object Manipulationcited by 2
  3. 2026Set-Supervised Diffusion Policy: Learning Action-Chunking Diffusion through Correctionscited by 1
  4. 2025Hybrid Imitation Learning: Teleoperation Augmentation Primitives that Policies Learn to Triggercited by 0
  5. 2026Instrumentation for Imitation Learning: Enhancing Training Datasets for Clothes Hanger Insertioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025DemoSpeedup: Accelerating Visuomotor Policies via Entropy-Guided Demonstration Acceleration
  2. 2026Test-time Adversarial Takeover: A Real-time Hijacking Interface against Robotic Diffusion Policies
  3. 2026STEP: Warm-Started Visuomotor Policies with Spatiotemporal Consistency Prediction
  4. 2025CDP: Towards Robust Autoregressive Visuomotor Policy Learning via Causal Diffusion
  5. 2018Reinforcement and Imitation Learning for Diverse Visuomotor Skills
  6. 2026Learning Coordinated Visuomotor Box-Pushing from Solo Demonstrations
  7. 2023Crossway Diffusion: Improving Diffusion-based Visuomotor Policy via Self-supervised Learning
  8. 2025Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution