Publications (5)
Seed2Scale: A Self-Evolving Data Engine for Embodied AI via Small to Large Model Synergy and Multimodal Evaluation
Cong Tai, Zhaoyu Zheng, Haixu Long +12
Existing data generation methods suffer from exploration limits, embodiment gaps, and low signal-to-noise ratios, leading to performance degradation during self-iteration. To addre…
RealMirror: A Comprehensive, Open-Source Vision-Language-Action Platform for Embodied AI
Cong Tai, Zhaoyu Zheng, Haixu Long +13
The emerging field of Vision-Language-Action (VLA) for humanoid robots faces several fundamental challenges, including the high cost of data acquisition, the lack of a standardized…
MirrorLimb: Implementing hand pose acquisition and robot teleoperation based on RealMirror
Cong Tai, Hansheng Wu, Haixu Long +4
In this work, we present a PICO-based robot remote operating framework that enables low-cost, real-time acquisition of hand motion and pose data, outperforming mainstream visual tr…
Mobile Robot Oriented Large-Scale Indoor Dataset for Dynamic Scene Understanding
Yifan Tang, Cong Tai, Fangxing Chen +5
Most existing robotic datasets capture static scene data and thus are limited in evaluating robots' dynamic performance. To address this, we present a mobile robot oriented large-s…
GRID: Scene-Graph-based Instruction-driven Robotic Task Planning
Zhe Ni, Xiaoxin Deng, Cong Tai +5
Recent works have shown that Large Language Models (LLMs) can facilitate the grounding of instructions for robotic task planning. Despite this progress, most existing works have pr…