arXiv AI
Jun 11
Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models
arXiv:2606. 11324v1 Announce Type: cross Abstract: We introduce Embodied-R1.
EmbodiedSmith: Scaling Embodied Data through Recursive Self-Improvement Flywheel in Simulation
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arXiv AI
Jul 14
Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model
arXiv:2607. 11643v1 Announce Type: cross Abstract: Recent foundation image and video generation models offer strong generalization and controllability, but their direct application to embodied scenarios is limited by requirements for multi-view consistency, geometric coherence, and robot embodiment constraints.
arXiv AI
Sep 30
Guava: Distilling Frontier VLMs into a Compact Agent through a Robotic Manipulation Harness
arXiv:2606.18363v3 Announce Type: replace-cross Abstract: Language models trained on large-scale vision-language data have demonstrated strong potential for embodied agents. Harnessing models through...
arXiv AI
Oct 7
SMART: Zero-Shot Sim-to-Real Articulated Object Manipulation via Large-Scale Synthetic Pretraining
SMART introduces a scalable system for zero‑shot sim‑to‑real articulated object manipulation by leveraging large‑scale synthetic pretraining. The core component, SMART‑Sim, is an articulation‑aware simulation platform that facilitates efficient task generation and demonstration collection. Using SMART‑Sim, the authors synthesize SMART‑Data, comprising over 1 million demonstrations across 44 task types, 5 robot setups, and 2,507 articulated objects, and demonstrate that a vision‑language‑action model pretrained on this data achieves competitive simulation performance and zero‑shot transfer to real‑world tasks.
arXiv AI
Jul 14
Pipette: An Embodied Simulation Platform, Benchmark, and Data-Efficient Augmentation Framework for Wet-Lab Robotics
arXiv:2606. 12936v2 Announce Type: replace-cross Abstract: Wet-lab robots can improve the reproducibility, throughput, and safety of biomedical experiments, but scaling their learning requires customizable simulators for safe and reproducible task generation, open editable laboratory assets, and efficient pipelines that turn limited demonstrations into usable training data.
arXiv AI
Sep 10
RoboCousin: Build Your Own Simulation Playground for Robust Bimanual Robotic Manipulation
RoboCousin is an extensible simulation platform that transforms user-provided observations into reusable assets, scenes, and expert trajectories for bimanual robotic manipulation. It converts object images into simulation-ready models with visual, collision, semantic, and physical metadata, automatically generates grasp candidates, and builds digital cousins that vary objects, backgrounds, layouts, and language instructions while preserving task-relevant affordances. The platform supports both tabletop and room-level scene construction, and the authors release RoboCousin-OBD with over 3,000 annotated objects and 50 backgrounds, generating more than one million expert trajectories across 50 tasks, with simulation and real-robot experiments demonstrating comparable annotation quality and effective sim-to-real transfer.
arXiv AI
Jul 7
Cortex: A Bidirectionally Aligned Embodied Agent Framework for Long-horizon Manipulation
arXiv:2607. 05377v1 Announce Type: cross Abstract: While recent Vision-Language-Action (VLA) models show promise toward generalist manipulation policies, they struggle with long-horizon tasks due to their Markovian nature-relying solely on current observations.
arXiv AI
Jun 18
Guava: An Effective and Universal Harness for Embodied Manipulation
arXiv:2606. 18363v1 Announce Type: cross Abstract: Language models trained on large-scale vision-language data have demonstrated strong potential for embodied agents.
arXiv AI
Jul 31
From Passive Video to Editable Experience: Physically Grounded Experience Synthesis for Embodied Intelligence
arXiv:2607. 26903v1 Announce Type: new Abstract: The key bottleneck in embodied AI is not model architecture but data.
arXiv AI
Jul 7
Embodied Operators and Benchmarking: Toward Reusable and Deployable Embodied Intelligence Systems
arXiv:2607. 03283v1 Announce Type: new Abstract: Embodied intelligence systems require not only end-to-end policy models, but also reusable functional modules that transform multimodal observations, robot states, human demonstrations, and task contexts into structured representations, decisions, trajectories, control references, and system services.
arXiv AI
Jun 12
An Embodied Simulation Platform, Benchmark, and Data-Efficient Augmentation Framework for Wet-Lab Robotics
arXiv:2606. 12936v1 Announce Type: cross Abstract: Wet-lab robots can improve the reproducibility, throughput, and safety of biomedical experiments, but scaling their learning requires customizable simulators for safe and reproducible task generation, open editable laboratory assets, and efficient pipelines that turn limited demonstrations into usable training data.
arXiv Computation and Language
Sep 11
Self-Evolving Embodied Agents via Skill-Harness Evolution
The paper introduces SHAPER, a self‑evolving framework that enables embodied agents to adapt to new environments without retraining the underlying foundation model. SHAPER keeps model parameters frozen and instead evolves reusable skills and a context‑code harness through rollouts in the target environment, allowing the same model to act as both planner and optimizer. Experiments on VLABench and ESI‑Bench demonstrate that this skill‑and‑harness optimization outperforms pure execution, supervised fine‑tuning, and test‑time scaling baselines, showing that self‑evolving adaptation is viable when model training is costly or impractical.