REBOOT: From Failure to Recovery - A Dataset and Benchmark for Precision Assembly
cs.RO
Submitted: 2026-09-18
Updated: 2026-09-18
Code: https://github.com/huggingface/lerobot
Project page: https://nanayawoa.github.io/REBOOT
Terminology
Sources
- Open X-Embodiment: Robotic Learning Datasets and RT-X Models
- RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction
- Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning
- RACER: Rich Language-Guided Failure Recovery Policies for Imitation Learning
- RoboFAC: A Comprehensive Framework for Robotic Failure Analysis and Correction
- REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction
- Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- Scaling Cross-Environment Failure Reasoning Data for Vision-Language Robotic Manipulation
- Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies
- One-Shot Imitation Learning
Related papers
- FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
- MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
- RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
- Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving