6 papers · 1 filter
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…
MLM: Learning Multi-task Loco-Manipulation Whole-Body Control for Quadruped Robot with Arm
Xin Liu, Bida Ma, Chenkun Qi +14
Whole-body loco-manipulation for quadruped robots with arms remains a challenging problem, particularly in achieving multi-task control. To address this, we propose MLM, a reinforc…
Skill-Nav: Enhanced Navigation with Versatile Quadrupedal Locomotion via Waypoint Interface
Dewei Wang, Chenjia Bai, Chenhui Li +4
Quadrupedal robots have demonstrated exceptional locomotion capabilities through Reinforcement Learning (RL), including extreme parkour maneuvers. However, integrating locomotion s…
Think Small, Act Big: Primitive Prompt Learning for Lifelong Robot Manipulation
Yuanqi Yao, Siao Liu, Haoming Song +7
Building a lifelong robot that can effectively leverage prior knowledge for continuous skill acquisition remains significantly challenging. Despite the success of experience replay…
MoMa-Kitchen: A 100K+ Benchmark for Affordance-Grounded Last-Mile Navigation in Mobile Manipulation
Pingrui Zhang, Xianqiang Gao, Yuhan Wu +6
In mobile manipulation, navigation and manipulation are often treated as separate problems, resulting in a significant gap between merely approaching an object and engaging with it…
AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems
AgiBot-World-Contributors, Qingwen Bu, Jisong Cai +49
We explore how scalable robot data can address real-world challenges for generalized robotic manipulation. Introducing AgiBot World, a large-scale platform comprising over 1 millio…