90 citations · 91 across the 5 of their papers we have counts for
3 papers · 1 filter
ZeroBot: Learning from Scratch in Minutes with Generative Real2Sim
Ivan Kapelyukh, Xiaohan Zhang, Stephen James +2
We present ZeroBot, a real2sim framework for learning a robot manipulation task from scratch in minutes under challenging conditions: zero human demonstrations, zero policy pre-tra…
Test-Time Spatial Reasoning for Robot Manipulation Using Generative Real-to-Sim
Ivan Kapelyukh, Yafei Hu, Ran Gong +6
Spatial reasoning is fundamental to general robot intelligence, as it enables robots to complete long-horizon tasks involving multi-object interaction. We introduce Simify, a train…
AnyTask: an Automated Task and Data Generation Framework for Advancing Sim-to-Real Policy Learning
Ran Gong, Xiaohan Zhang, Jinghuan Shang +11
Generalist robot learning remains constrained by data: large-scale, diverse, and high-quality interaction data are expensive to collect in the real world. While simulation has beco…