VOMMI: Collecting and Leveraging Portable Demonstrations for Mobile Manipulation
cs.RO, cs.AI
Submitted: 2026-10-06
Updated: 2026-10-06
Sources
- OpenHLM: An Empirical Recipe for Whole-Body Humanoid Loco-Manipulation
- $\omega$-0: A Latent Predictive World Action Model for Concurrent Humanoid Loco-Manipulation
- MotionWAM: Towards Foundation World Action Models for Real-Time Humanoid Loco-Manipulation
- Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots
- FastUMI: A Scalable and Hardware-Independent Universal Manipulation Interface with Dataset
- What Enables In-Context Behavior Prompting for Manipulation?
- HoMMI: Learning Whole-Body Mobile Manipulation from Human Demonstrations
- Mobile UMI: Cross-View Diffusion Policy with Decoupled Kinematics for Mobile Manipulation
- EgoHumanoid: Unlocking In-the-Wild Loco-Manipulation with Robot-Free Egocentric Demonstration
- UMI on Legs: Making Manipulation Policies Mobile with Manipulation-Centric Whole-body Controllers
- HomeRobot: Open-Vocabulary Mobile Manipulation
- QUAR-VLA: Vision-Language-Action Model for Quadruped Robots
- Look, Focus, Act: Efficient and Robust Robot Learning via Human Gaze and Foveated Vision Transformers
- VGGT-SLAM 2.0: Real-time Dense Feed-forward Scene Reconstruction
- VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation
- EgoMimic: Scaling Imitation Learning via Egocentric Video
- MASt3R-SLAM: Real-Time Dense SLAM with 3D Reconstruction Priors
- Continuous 3D Perception Model with Persistent State
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
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
- ARC: A Reasoning Recipe for Robot Foundation Models
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies