mlsanityData to 14 Oct 2026

A Survey on Imitation Learning for Contact-Rich Tasks in Robotics

arXiv 2506.13498 ↗First posted 16 Jun 2025cs.RO cs.HC cs.LGcited by 14

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

Abstract (arXiv)

This paper comprehensively surveys research trends in imitation learning for contact-rich robotic tasks. Contact-rich tasks, which require complex physical interactions with the environment, represent a central challenge in robotics due to their nonlinear dynamics and sensitivity to small positional deviations. The paper examines demonstration collection methodologies, including teaching methods and sensory modalities crucial for capturing subtle interaction dynamics. We then analyze imitation learning approaches, highlighting their applications to contact-rich manipulation. Recent advances in multimodal learning and foundation models have significantly enhanced performance in complex contact tasks across industrial, household, and healthcare domains. Through systematic organization of current research and identification of challenges, this survey provides a foundation for future advancements in contact-rich robotic manipulation.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Placed in Robot manipulation imitation learning, one of 13 directions in Offline RL and imitation learning from data. Builds on 151 of its 305 references that are in the map. First posted on arXiv 16 Jun 2025.

Builds on

151 of 305 references.

Closest ancestors · 24

Same direction, newest first

  1. 2025Interactive Imitation Learning for Dexterous Robotic Manipulation: Challenges and Perspectives -- A Survey30 May
  2. 2025Adaptive Wiping: Adaptive contact-rich manipulation through few-shot imitation learning with Force-Torque feedback and pre-trained object representations9 May
  3. 2025Dexterous Manipulation through Imitation Learning: A Survey4 Apr
  4. 2024Dream to Manipulate: Compositional World Models Empowering Robot Imitation Learning with Imagination19 Dec
  5. 2024ForceMimic: Force-Centric Imitation Learning with Force-Motion Capture System for Contact-Rich Manipulation10 Oct
  6. 2024Mamba as a motion encoder for robotic imitation learning4 Sep
  7. 2024Conditional Variational Auto Encoder Based Dynamic Motion for Multi-task Imitation Learning24 May
  8. 2024JUICER: Data-Efficient Imitation Learning for Robotic Assembly4 Apr
  9. 2024DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation12 Mar
  10. 2024Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation4 Jan
  11. 2023LOTUS: Continual Imitation Learning for Robot Manipulation Through Unsupervised Skill Discovery3 Nov
  12. 2023Multimodal and Force-Matched Imitation Learning with a See-Through Visuotactile Sensor2 Nov
12 more
  1. 2023BridgeData V2: A Dataset for Robot Learning at Scale24 Aug
  2. 2023Seq2Seq Imitation Learning for Tactile Feedback-based Manipulation5 Mar
  3. 2023MimicPlay: Long-Horizon Imitation Learning by Watching Human Play24 Feb
  4. 2022CACTI: A Framework for Scalable Multi-Task Multi-Scene Visual Imitation Learning12 Dec
  5. 2022A System for Imitation Learning of Contact-Rich Bimanual Manipulation Policies1 Aug
  6. 2022Learning Deformable Object Manipulation from Expert Demonstrations20 Jul
  7. 2022BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning4 Feb
  8. 2021Coarse-to-Fine Imitation Learning: Robot Manipulation from a Single Demonstration13 May
  9. 2021LazyDAgger: Reducing Context Switching in Interactive Imitation Learning31 Mar
  10. 2020Imitation Learning for High Precision Peg-in-Hole Tasks26 Dec
  11. 2019Learning One-Shot Imitation from Humans without Humans4 Nov
  12. 2019Deep Imitation Learning of Sequential Fabric Smoothing From an Algorithmic Supervisor23 Sep

Other references · 127

  1. 2017Attention Is All You Needcited by 60,361
  2. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,418
  3. 2023RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Controlcited by 3,080
  4. 2024OpenVLA: An Open-Source Vision-Language-Action Modelcited by 2,887
  5. 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,838
  6. 2023PaLM-E: An Embodied Multimodal Language Modelcited by 2,071
  7. 2022RT-1: Robotics Transformer for Real-World Control at Scalecited by 2,061
  8. 2020Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problemscited by 1,920
  9. 2016Generative Adversarial Imitation Learningcited by 1,597
  10. 2021Ego4D: Around the World in 3,000 Hours of Egocentric Videocited by 1,556
  11. 2017Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real Worldcited by 1,498
  12. 2024Octo: An Open-Source Generalist Robot Policycited by 1,484
38 more
  1. 2023LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learningcited by 1,410
  2. 2021Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learningcited by 998
  3. 2015End-to-End Training of Deep Visuomotor Policiescited by 875
  4. 2017Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrationscited by 715
  5. 2019RLBench: The Robot Learning Benchmark & Learning Environmentcited by 689
  6. 2017Sim-to-Real Transfer of Robotic Control with Dynamics Randomizationcited by 672
  7. 2022Compositional Visual Generation with Composable Diffusion Modelscited by 624
  8. 2021CLIPort: What and Where Pathways for Robotic Manipulationcited by 622
  9. 2021CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Taskscited by 584
  10. 2022Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulationcited by 551
  11. 2021Implicit Behavioral Cloningcited by 452
  12. 2018Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Networkcited by 420
  13. 2021Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulationcited by 407
  14. 2022DayDreamer: World Models for Physical Robot Learningcited by 400
  15. 2021Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learningcited by 371
  16. 2023Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulationcited by 364
  17. 2023Vision-Language Foundation Models as Effective Robot Imitatorscited by 349
  18. 2017Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewardscited by 319
  19. 2017Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperationcited by 289
  20. 2018HG-DAgger: Interactive Imitation Learning with Human Expertscited by 266
  21. 2017One-Shot Imitation Learningcited by 233
  22. 2017One-Shot Visual Imitation Learning via Meta-Learningcited by 228
  23. 2023Foundation Models in Robotics: Applications, Challenges, and the Futurecited by 216
  24. 2021iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Taskscited by 194
  25. 2023RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shotcited by 183
  26. 2018Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networkscited by 174
  27. 2024Consistency Policy: Accelerated Visuomotor Policies via Consistency Distillationcited by 166
  28. 2018One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learningcited by 148
  29. 2019A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithmscited by 142
  30. 2022What Matters in Language Conditioned Robotic Imitation Learning over Unstructured Datacited by 138
  31. 2023Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functionscited by 131
  32. 2025HAMSTER: Hierarchical Action Models For Open-World Robot Manipulationcited by 130
  33. 2024AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulationcited by 125
  34. 2024Yell At Your Robot: Improving On-the-Fly from Language Correctionscited by 124
  35. 2023RoboCat: A Self-Improving Generalist Agent for Robotic Manipulationcited by 111
  36. 2016A Differentiable Physics Engine for Deep Learning in Roboticscited by 108
  37. 2021ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learningcited by 108
  38. 2017Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstrationcited by 100

50 most cited of 127 All 127 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 13.

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  1. 2026TacVLA: Contact-Aware Tactile Fusion for Robust Vision-Language-Action Manipulationcited by 19
  2. 2025Bi-VLA: Bilateral Control-Based Imitation Learning via Vision-Language Fusion for Action Generationcited by 3
  3. 2026Bi-HIL: Bilateral Control-Based Multimodal Hierarchical Imitation Learning via Subtask-Level Progress Rate and Keyframe Memory for Long-Horizon Contact-Rich Robotic Manipulationcited by 2
  4. 2026ForeDiffusion: Foresight-Conditioned Diffusion Policy via Future View Construction for Robot Manipulationcited by 1
  5. 2026Lifelong Imitation Learning with Multimodal Latent Replay and Incremental Adjustmentcited by 1
  6. 2026RoCo Challenge at AAAI 2026: Benchmarking Robotic Collaborative Manipulation for Assembly Towards Industrial Automationcited by 0
  7. 2026Spacetime Optimal-Transport Attention for Visuo-Haptic Imitation Learning of Contact-Rich Manipulationcited by 0
  8. 2026VE2VF: Vision-Enabled to Vision-Free Distillation via Real-world Reinforcement Learning for Robust Contact-Rich Manipulationcited by 0
  9. 2026NDPP-Grasp: Non-Differentiable Physical Plausibility Constraint-Guided Task-Oriented Dexterous Grasp Generationcited by 0
  10. 2026Critical Interval MSE: Toward Reliable Offline Validation for Robot Manipulation Policiescited by 0
  11. 2026CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Liftscited by 0
  12. 2026A Hierarchical Approach to Imitation Learning for Manipulation Tasks Requiring Time Varying Forcescited by 0
2 more
  1. 2026Bi-MoDe: Bilateral Control-based Imitation Learning via Modifier-Conditioned Decoding for Modulation of Execution Speed and Contact Intensitycited by 0
  2. 2026Equivariant Visual-Tactile Diffusion Policy for Contact-Rich Manipulationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Robotic Manipulation via Imitation Learning: Taxonomy, Evolution, Benchmark, and Challenges
  2. 2026One-Shot Learning from Demonstration of Contact-Rich Robotic Manipulation by Identifying Physical Interactions
  3. 2025On the Importance of Tactile Sensing for Imitation Learning: A Case Study on Robotic Match Lighting
  4. 2026Contact-Aware Imitation Learning Through Contact Factorization
  5. 2023Teaching contact-rich tasks from visual demonstrations by constraint extraction ↗
  6. 2024A Comparison of Imitation Learning Algorithms for Bimanual Manipulation
  7. 2024Should We Learn Contact-Rich Manipulation Policies from Sampling-Based Planners?
  8. 2025RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments