mlsanityData to 7 Oct 2026

Goal-conditioned dual-action imitation learning for dexterous dual-arm robot manipulation

arXiv 2203.09749 ↗First posted 18 Mar 2022cs.RO cs.CVcited by 21

On the map: Offline RL and imitation learning from data → Robot manipulation imitation learning

Abstract (arXiv)

Long-horizon dexterous robot manipulation of deformable objects, such as banana peeling, is a problematic task because of the difficulties in object modeling and a lack of knowledge about stable and dexterous manipulation skills. This paper presents a goal-conditioned dual-action (GC-DA) deep imitation learning (DIL) approach that can learn dexterous manipulation skills using human demonstration data. Previous DIL methods map the current sensory input and reactive action, which often fails because of compounding errors in imitation learning caused by the recurrent computation of actions. The method predicts reactive action only when the precise manipulation of the target object is required (local action) and generates the entire trajectory when precise manipulation is not required (global action). This dual-action formulation effectively prevents compounding error in the imitation learning using the trajectory-based global action while responding to unexpected changes in the target object during the reactive local action. The proposed method was tested in a real dual-arm robot and successfully accomplished the banana-peeling task. Data from this and related works are available at: https://sites.google.com/view/multi-task-fine.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Placed in Robot manipulation imitation learning, one of 13 directions in Offline RL and imitation learning from data. Builds on 26 of its 74 references that are in the map. First posted on arXiv 18 Mar 2022.

Builds on

26 of 74 references.

Closest ancestors · 4

Same direction, newest first

  1. 2022Training Robots without Robots: Deep Imitation Learning for Master-to-Robot Policy Transfer19 Feb
  2. 2022Memory-based gaze prediction in deep imitation learning for robot manipulation10 Feb
  3. 2021Transformer-based deep imitation learning for dual-arm robot manipulation1 Aug
  4. 2020Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations13 Mar

Other references · 22

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2016Generative Adversarial Imitation Learningcited by 1,576
  4. 2017Random Erasing Data Augmentationcited by 1,235
  5. 2017Hindsight Experience Replaycited by 1,096
  6. 2019On the Variance of the Adaptive Learning Rate and Beyondcited by 763
  7. 2020Quantifying Attention Flow in Transformerscited by 759
  8. 2017End-to-end Driving via Conditional Imitation Learningcited by 479
  9. 2019Learning Latent Plans from Playcited by 310
  10. 2017Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperationcited by 286
  11. 2017Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translationcited by 167
  12. 2019Goal-conditioned Imitation Learningcited by 159
10 more
  1. 2015Deep Spatial Autoencoders for Visuomotor Learningcited by 149
  2. 2019AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videoscited by 105
  3. 2019IRIS: Implicit Reinforcement without Interaction at Scale for Learning Control from Offline Robot Manipulation Datacited by 85
  4. 2014Batch Informed Trees (BIT*): Sampling-based Optimal Planning via the Heuristically Guided Search of Implicit Random Geometric Graphscited by 38
  5. 2020Guided Uncertainty-Aware Policy Optimization: Combining Learning and Model-Based Strategies for Sample-Efficient Policy Learningcited by 22
  6. 2020Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environmentscited by 19
  7. 2016Recurrent Mixture Density Network for Spatiotemporal Visual Attentioncited by 16
  8. 2021Gaze-based dual resolution deep imitation learning for high-precision dexterous robot manipulationcited by 16
  9. 2021Learning Periodic Tasks from Human Demonstrationscited by 10
  10. 2017Reactive Trajectory Generation in an Unknown Environmentcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 5; 2025: 12; 2026: 2.

21 papers.

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  1. 2023Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardwarecited by 1,490
  2. 2024Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperationcited by 377
  3. 2025FlowVLA: Visual Chain of Thought-based Motion Reasoning for Vision-Language-Action Modelscited by 50
  4. 2024ForceMimic: Force-Centric Imitation Learning with Force-Motion Capture System for Contact-Rich Manipulationcited by 36
  5. 2025Dexterous Manipulation through Imitation Learning: A Surveycited by 18
  6. 2025Act2Goal: From World Model To General Goal-conditioned Policycited by 18
  7. 2023f-Policy Gradients: A General Framework for Goal Conditioned RL using f-Divergencescited by 14
  8. 2024DAG-Plan: Generating Directed Acyclic Dependency Graphs for Dual-Arm Cooperative Planningcited by 14
  9. 2025METIS: Multi-Source Egocentric Training for Integrated Dexterous Vision-Language-Action Modelcited by 9
  10. 2025Learning Bimanual Manipulation via Action Chunking and Inter-Arm Coordination with Transformerscited by 8
  11. 2024APEX: Ambidextrous Dual-Arm Robotic Manipulation Using Collision-Free Generative Diffusion Modelscited by 7
  12. 2024Vegetable Peeling: A Case Study in Constrained Dexterous Manipulationcited by 7
9 more
  1. 2025Lemmanaid: Neuro-Symbolic Lemma Conjecturingcited by 5
  2. 2025UniConFlow: A Unified Constrained Flow-Matching Framework for Certified Motion Planningcited by 4
  3. 2025Gaze-Guided Task Decomposition for Imitation Learning in Robotic Manipulationcited by 3
  4. 2025Enhancing Reusability of Learned Skills for Robot Manipulation via Gaze Information and Motion Bottleneckscited by 2
  5. 2025ChicGrasp: Imitation-Learning based Customized Dual-Jaw Gripper Control for Delicate, Irregular Bio-products Manipulationcited by 1
  6. 2026Exploration-assisted Bottleneck Transition Toward Robust and Data-efficient Deformable Object Manipulationcited by 1
  7. 2025Learning Dual-Arm Coordination for Grasping Large Flat Objectscited by 0
  8. 2025Imitation Learning for Active Neck Motion Enabling Robot Manipulation beyond the Field of Viewcited by 0
  9. 2026Scalable Dexterous Robot Learning with AR-based Remote Human-Robot Interactionscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Multi-task real-robot data with gaze attention for dual-arm fine manipulation
  2. 2025Interactive Imitation Learning for Dexterous Robotic Manipulation: Challenges and Perspectives -- A Survey
  3. 2020Goal-Conditioned End-to-End Visuomotor Control for Versatile Skill Primitives
  4. 2025ObjectVLA: End-to-End Open-World Object Manipulation Without Demonstration
  5. 2022One-Shot Domain-Adaptive Imitation Learning via Progressive Learning
  6. 2022Learning Sensorimotor Primitives of Sequential Manipulation Tasks from Visual Demonstrations
  7. 2025One-Shot Dual-Arm Imitation Learning
  8. 2025Annotation-Free One-Shot Imitation Learning for Multi-Step Manipulation Tasks