I3L: Iterative Interactive Imitation Learning for Whole-Body Mobile Manipulation
cs.RO, cs.AI
Submitted: 2026-10-13
Updated: 2026-10-13
Comments: Project website: https://i-3l.github.io/
Project page: https://i-3l.github.io
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- Interactive Imitation Learning in Robotics: A Survey
- Human-in-the-Loop Imitation Learning using Remote Teleoperation
- RoboCopilot: Human-in-the-loop Interactive Imitation Learning for Robot Manipulation
- BEHAVIOR-1K: A Human-Centered, Embodied AI Benchmark with 1,000 Everyday Activities and Realistic Simulation
- Open-TeleVision: Teleoperation with Immersive Active Visual Feedback
- UMI on Legs: Making Manipulation Policies Mobile with Manipulation-Centric Whole-body Controllers
- ACE: A Cross-Platform Visual-Exoskeletons System for Low-Cost Dexterous Teleoperation
- TeleMoMa: A Modular and Versatile Teleoperation System for Mobile Manipulation
- Human-Robot Copilot for Data-Efficient Imitation Learning
- DexHiL: A Human-in-the-Loop Framework for Vision-Language-Action Model Post-Training in Dexterous Manipulation
- LazyDAgger: Reducing Context Switching in Interactive Imitation Learning
- Multi-Task Interactive Robot Fleet Learning with Visual World Models
- FlowCorrect: Efficient Interactive Correction of Generative Flow Policies for Robotic Manipulation
- Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning
- TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning
- OmniH2O: Universal and Dexterous Human-to-Humanoid Whole-Body Teleoperation and Learning
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