6 papers · 1 filter
EgoExplorer: A Vision-Motion-Touch Observatory for Human Loco-Manipulation In Situ
Yunsong Zhou, Xuekun Jiang, Haiqi Shen +11
Learning humanoid loco-manipulation from human demonstrations rests on observing how locomotion, posture, and object interaction evolve together as tasks unfold. Scaling collection…
RoboBridge: A Self-Evolving Embodied Agent Framework for Sim-to-Real Transfer
Chenxi Li, Zhangrui Zhao, Rui Li +8
A key challenge in bringing embodied intelligence into the real world is transferring capabilities from simulation to reality and enabling agents to continually adapt after deploym…
WOLF: World Model Guided LiDAR Exploration with Predictive Frontiers
Yuyang Tian, Penghui Yang, Pengyuan Wu +7
LiDAR-based unmanned aerial vehicle (UAV) exploration builds maps by continually selecting where to observe next. However, decisions based on the measured map provide limited fores…
Xiaomi-Robotics-0: An Open-Sourced Vision-Language-Action Model with Real-Time Execution
Rui Cai, Jun Guo, Xinze He +20
In this report, we introduce Xiaomi-Robotics-0, an advanced vision-language-action (VLA) model optimized for high performance and fast and smooth real-time execution. The key to ou…
FastUMI-100K: Advancing Data-driven Robotic Manipulation with a Large-scale UMI-style Dataset
Kehui Liu, Zhongjie Jia, Yang Li +14
Data-driven robotic manipulation learning depends on large-scale, high-quality expert demonstration datasets. However, existing datasets, which primarily rely on human teleoperated…
Trajectory Conditioned Cross-embodiment Skill Transfer
YuHang Tang, Yixuan Lou, Pengfei Han +4
Learning manipulation skills from human demonstration videos presents a promising yet challenging problem, primarily due to the significant embodiment gap between human body and ro…