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A single 500-hour visual-tactile dataset boosts zero-shot contact prediction from 13% to 38% IoU and quadruples robot manipulation success rates, proving scale and consistency are paramount for embodied learning.
The preliminary results of teleoperating Astrobee in a custom zero-gravity MuJoCo-based International Space Station (ISS) simulator through ten repeated trials of transporting a rigid ISS Cargo Transfer Bag (CTB) are presented.
TANGO enables humanoid robots to navigate cluttered spaces with unprecedented language-guided precision, achieving state-of-the-art performance without real-world training.
Standard 2D vision-language models can reliably plan precise 3D robot trajectories simply by enforcing multi-view 2D waypoint consistency and applying classic geometric triangulation.
Substantial challenges in task generalization and visuomotor robustness are revealed, highlighting critical gaps in current dexterous manipulation benchmarks.
