5 papers · 1 filter
GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation
AgiBot Research Team, Renhang Liu, Wenzhi Zhao +42
World-action models (WAM) predict future states to guide robot actions, enabling learning from both action-free video and action-labeled interaction. Most inherit pretrained video…
CR-Solver: GPU-Accelerated Kinematics Solver for Tendon-driven Continuum Robots
Heqing Yang, Yang Yi, Linqing Zhong +2
Continuum robots provide intrinsic compliance, high dexterity, and safe physical interaction, enabling navigation and manipulation in confined and unstructured environments. Despit…
EVA-Client: A Unified Data Collection, Inference, and Deployment Framework for Embodied Policies on Real Robots
Heqing Yang, Yang Yi, Liyao Wang +8
We present EVA-Client, an open-source framework for deployment, data collection, and evaluation of trained manipulation policies on real robots. Sitting between a policy server and…
Libra-VLA: Achieving Learning Equilibrium via Asynchronous Coarse-to-Fine Dual-System
Yifei Wei, Linqing Zhong, Yi Liu +4
Vision-Language-Action (VLA) models are a promising paradigm for generalist robotic manipulation by grounding high-level semantic instructions into executable physical actions. How…
ACoT-VLA: Action Chain-of-Thought for Vision-Language-Action Models
Linqing Zhong, Yi Liu, Yifei Wei +4
Vision-Language-Action models have emerged as essential generalist robot policies for diverse manipulation tasks, conventionally relying on directly translating multimodal inputs i…