2 citations · 3 across the 4 of their papers we have counts for
11 papers · 1 filter
The Neverwhere Visual Parkour Benchmark Suite
Ziyu Chen, Henghui Bao, Haoran Chang +12
State-of-the-art visual locomotion controllers are increasingly capable at handling complex visual environments, making evaluating their real-world performance before deployment in…
Lucid-XR: An Extended-Reality Data Engine for Robotic Manipulation
Yajvan Ravan, Adam Rashid, Alan Yu +8
We introduce Lucid-XR, a generative data engine for creating diverse and realistic-looking multi-modal data to train real-world robotic systems. At the core of Lucid-XR is vuer, a…
Human-Robot Copilot for Data-Efficient Imitation Learning
Rui Yan, Zaitian Gongye, Lars Paulsen +2
Collecting human demonstrations via teleoperation is a common approach for teaching robots task-specific skills. However, when only a limited number of demonstrations are available…
WildLMa: Long Horizon Loco-Manipulation in the Wild
Ri-Zhao Qiu, Yuchen Song, Xuanbin Peng +8
'In-the-wild' mobile manipulation aims to deploy robots in diverse real-world environments, which requires the robot to (1) have skills that generalize across object configurations…
Visual Manipulation with Legs
Xialin He, Chengjing Yuan, Wenxuan Zhou +3
Animals use limbs for both locomotion and manipulation. We aim to equip quadruped robots with similar versatility. This work introduces a system that enables quadruped robots to in…
Helpful DoggyBot: Open-World Object Fetching using Legged Robots and Vision-Language Models
Qi Wu, Zipeng Fu, Xuxin Cheng +2
Learning-based methods have achieved strong performance for quadrupedal locomotion. However, several challenges prevent quadrupeds from learning helpful indoor skills that require…