Policy-Calibrated DAgger: Offline Calibrated Noise Injection for Imitation Learning
cs.RO
Submitted: 2026-09-24
Updated: 2026-09-24
Terminology
Sources
- Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots
- RoboCopilot: Human-in-the-loop Interactive Imitation Learning for Robot Manipulation
- FACTR: Force-Attending Curriculum Training for Contact-Rich Policy Learning
- Echo: An Open-Source, Low-Cost Teleoperation System with Force Feedback for Dataset Collection in Robot Learning
- To the Noise and Back: Diffusion for Shared Autonomy
- WM-DAgger: Enabling Efficient Data Aggregation for Imitation Learning with World Models
- Diffusion Meets DAgger: Supercharging Eye-in-hand Imitation Learning
- DADAgger: Disagreement-Augmented Dataset Aggregation
- Don't Start from Scratch: Behavioral Refinement via Interpolant-based Policy Diffusion
- Sim-and-Real Co-Training: A Simple Recipe for Vision-Based Robotic Manipulation
- REvolveR: Continuous Evolutionary Models for Robot-to-robot Policy Transfer
- HERD: Continuous Human-to-Robot Evolution for Learning from Human Demonstration
- SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations
- Splat-MOVER: Multi-Stage, Open-Vocabulary Robotic Manipulation via Editable Gaussian Splatting
- RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation
- Deep Reactive Policy: Learning Reactive Manipulator Motion Planning for Dynamic Environments
- MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
- DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning
- SAPS: Shared Autonomy for Policy Steering by Blending Teleoperation with a Pretrained VLA
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