6 papers
LabDex: A Hierarchical Benchmark for Dexterous Manipulation in Laboratories
Zhipeng Tang, Sihang Chen, Sha Zhang +11
Autonomous laboratories hold great promise for accelerating scientific discovery. To achieve this vision, robots are supposed to dexterously manipulate diverse labware and instrume…
ReTouch: Empowering Contact-Rich Dexterous Manipulation with Online-Refined Tactile Prediction
Shiqi Zhang, Xin Zhang, Yedong Shen +9
Fusing tactile signals has proven effective for contact-rich manipulation, enabling robots to perceive contact states and adapt to rapidly changing physical interactions. Yet effec…
iFLYTEK-Embodied-Omni Technical Report
Yuan Zhang, Jingfei Ni, Guanchen Lu +12
General-purpose embodied agents must understand multimodal instructions, anticipate how their environment will evolve, and produce precise control actions over extended horizons. E…
GEAR-VLA: Learning Geometry-Aware Action Representations for Generalizable Robotic Manipulation
Yuan Zhang, Shiqi Zhang, Yedong Shen +11
Vision-Language-Action (VLA) models achieve strong benchmark performance but still struggle in real-world deployment with unseen objects, background shifts, and different robot emb…
iFlyBot-VLM Technical Report
Xin Nie, Zhiyuan Cheng, Yuan Zhang +4
We introduce iFlyBot-VLM, a general-purpose Vision-Language Model (VLM) used to improve the domain of Embodied Intelligence. The central objective of iFlyBot-VLM is to bridge the c…
iFlyBot-VLA Technical Report
Yuan Zhang, Chenyu Xue, Wenjie Xu +3
We introduce iFlyBot-VLA, a large-scale Vision-Language-Action (VLA) model trained under a novel framework. The main contributions are listed as follows: (1) a latent action model…