Robotics

This paper introduces SPARC, a risk-aware framework that automatically labels robot demonstrations with structured spatial annotations and assigns reliability scores.

This paper presents ArtiTwinSplat, a framework for constructing articulated, photo-realistic digital twins of objects directly from RGB-D videos in real-world environments.

This paper proposes a world model architecture called WEAVER that achieves state-of-the-art results on robotic manipulation tasks.

The paper proposes VERA, a decoupled policy that uses an action-free video world model combined with an embodiment-specific Inverse Dynamics Model (IDM) to achieve generalizable, zero-shot robot contr…

A single robot platform, Handroid, is introduced that can function as both a dexterous hand and a humanoid robot, with interchangeable control and learning frameworks.

This paper presents Mana, a sim-to-real framework for dexterous articulated tool manipulation.

Qwen-VLA introduces a unified embodied foundation model that extends vision-language understanding to continuous action generation, enabling robust, multi-task generalization across diverse robotic ta…

This paper proposes robot-factored world models for action-conditioned video prediction in robotics, which factor out action realization and robot rendering to avoid learning the realization process a…

This paper organizes embodied data sources for multimodal foundation models into a pyramid, focusing on real-robot, UMI-style, egocentric and exocentric, simulation, and general vision-language data.

This survey provides a comprehensive, structured review of safety research in Embodied AI, analyzing attacks and defenses across the entire embodied pipeline to guide the development of safe, robust,…

The paper proposes a new framework, DyMD, to improve video generation and embodied prediction by adapting teacher supervision and critic fitting to the evolving student.

The paper introduces TouchSafeBench, a physics-grounded benchmark, to evaluate collision grounding—the ability to predict robot-human collisions—and finds that current Vision-Language Models (VLMs) ar…

This paper presents a method for modeling and manipulating plant branches in agricultural robotics.

The paper presents Ropedia W0, a world model that enables embodied agents to anticipate action consequences across diverse embodiments.

WorldOlympiad is introduced as a benchmark for evaluating video-based world models across physical faithfulness, geometric consistency, and interaction fidelity.

This paper introduces a method to improve 3D world models for robotics by combining learned stereo depth with a joint factor graph and training a world model that jointly predicts multi-view RGB and d…

Qwen-RobotWorld is a language-conditioned video world model for embodied intelligence that predicts physically grounded future visual trajectories.

This paper introduces LingBot-Video, a video pretraining paradigm for embodied intelligence using a DiT-based approach, Mixture-of-Experts framework, and extensive robot-oriented data.

This paper proposes a compact, explicit interface for humanoid robots that enables diverse manipulation skills and demonstrates its feasibility through natural-language-driven task roll-outs.

The paper proposes an iCEM+TL framework that combines the Sample-efficient Cross-Entropy Method with Transfer Learning and Reward Redesign to improve robotic motion planning for complex tasks like sta…