arXiv
LoopWAM: Closed-Loop Generalist Policy Improvement from Deployment Rollouts
Scaling expert demonstrations alone does not enable generalist robot policies to improve from deploy...
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arXiv
EgoExplorer: A Vision-Motion-Touch Observatory for Human Loco-Manipulation In Situ
Learning humanoid loco-manipulation from human demonstrations rests on observing how locomotion, pos...
arXiv
What Matters in Quality-Aware VLA Pretraining: A Benchmark and Empirical Study
How should demonstration quality be used during vision-language-action (VLA) pretraining to improve ...
arXiv
LIBERO-RIG: A Hardware-Setup Robustness Benchmark for Vision-Language-Action Models
Robot policies are expected to generalize across deployment environments, including variations in th...
arXiv
Who Improves the Robot? Toward Physical Recursive Self-Improvement
Robots are increasingly autonomous in task execution, yet their improvement remains largely human-dr...
arXiv
Splat2Act: From Captured Scenes to Personalized VLA Manipulation
A user who brings a generalist manipulation policy into their home or office wants it to pick up the...
arXiv
Chronos Policy: Learning Robot Policies on Physical Time
Robot policies often convert sensing and control into fixed-rate observation-action sequences, leavi...
arXiv
Beyond the Snowflakes: Disentangling Weather Effects from Confounding Meta-Factors in LiDAR Object Detection
Light Detection and Ranging (LiDAR) is critical for autonomous perception, yet its performance is kn...
arXiv
CSF: Contextual Safety Filtering for Motion Generators
Text-conditioned motion generators produce trackable whole-body motion, but they have no notion of s...
arXiv
A Balanced Data Diet: Addressing the Exploration Bottleneck in Mega-Scale RL for Robot Control
General-purpose robots must perform a wide range of tasks from agile locomotion to dexterous manipul...
arXiv
VersaCamVLA: Camera-Configurable VLA Policies for Robotic Manipulation
Vision-Language-Action (VLA) models have emerged as powerful foundations for robotic manipulation, b...
arXiv
VioLA: Learning Generalist Humanoid Control Policies from Human Data
Teaching a humanoid to follow instructions with its whole body runs into two obstacles.
arXiv
FAITH: Feasibility-Aware Safety-Filtered RL for High-Dimensional Systems
Safe reinforcement learning commonly places safety and task performance in the same policy objective...
arXiv
RoboRSI: Stable, efficient, and reusable robot self-evolution in complex real-world environments
A generalist robot should not only perform diverse tasks but also improve through experience, turnin...
arXiv
Dex-One2Many: Learning Dexterous Manipulation from a Single Human Demonstration
While learning dexterous manipulation from a single human video offers a promising alternative to co...