REVOLVE: An Automated Closed-Loop Framework for Evolving Robot Manipulation with Minimal Human Intervention
cs.RO
Submitted: 2026-09-13
Updated: 2026-09-17
Terminology
Sources
- Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
- RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
- OpenVLA: An Open-Source Vision-Language-Action Model
- RoboDreamer: Learning Compositional World Models for Robot Imagination
- Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
- Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots
- EgoScale: Scaling Dexterous Manipulation with Diverse Egocentric Human Data
- MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
- What Matters in Learning from Offline Human Demonstrations for Robot Manipulation
- DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
- AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- Human-in-the-Loop Imitation Learning using Remote Teleoperation
- ThriftyDAgger: Budget-Aware Novelty and Risk Gating for Interactive Imitation Learning
- robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
- AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents
- AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems
- RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation
- ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy
- $\pi^{*}_{0.6}$: a VLA That Learns From Experience
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