8 papers · 1 filter
GTA-2: A Multi-VLM Framework for Synthesizing Robot Manipulation Skills via Grounded Task Axes
M. Yunus Seker, Shobhit Aggarwal, Ruwan Wickramarachchi +2
Robotic manipulation tasks are often decomposed into behaviors or skills. However, one often needs to predefine these behaviors for specific tasks or try to cover a wide range of t…
ControlledShifts: Towards Standardizing Robustness Evaluation in Trajectory Prediction Under Distribution Shifts
Ingrid Navarro, Pablo Ortega-Kral, Yutong Duan +2
Trajectory prediction is central to safety in autonomous driving, yet learning-based predictors tend to degrade sharply when encountering scenarios poorly represented by their trai…
ScenarioCharacterization: A Modular Toolkit for Characterizing Safety across Trajectory Datasets
Ingrid Navarro, Yutong Duan, Jonathan Francis +1
We introduce ScenarioCharacterization, an open-source framework for automated, dataset-agnostic profiling of driving scenarios in trajectory datasets. Our framework is packaged as…
GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks
Kaiyuan Chen, Shuangyu Xie, Letian Fu +21
For robots to work reliably in commercial and industrial applications, recent advances in agentic coding systems have potential to combine interpretable robot programming with the…
VibeAct: Vibration to Actions for Contact-Rich Reactive Robot Dexterity
Yuemin Mao, Uksang Yoo, Jean Oh +2
Dexterous manipulation depends on contact events that are fast, local, and often visually occluded. Piezoelectric microphones provide compact, high-bandwidth sensing of these inter…
Recover, Discover, Plan: Learning Skills and Concepts from Robot Failures
Bowen Li, Mayank Mishra, Y. Isabel Liu +7
Intelligent robots should not only recover from failures, but also acquire the abstract knowledge needed to avoid them in the future. While reinforcement learning (RL) can learn re…
RIO: Flexible Real-Time Robot I/O for Cross-Embodiment Robot Learning
Pablo Ortega-Kral, Eliot Xing, Arthur Bucker +13
Despite recent efforts to collect multi-task, multi-embodiment datasets, to design recipes for training Vision-Language-Action models (VLAs), and to showcase these models on differ…
SOFTMAP: Sim2Real Soft Robot Forward Modeling via Topological Mesh Alignment and Physics Prior
Ziyong Ma, Uksang Yoo, Jonathan Francis +3
While soft robot manipulators offer compelling advantages over rigid counterparts, including inherent compliance, safe human-robot interaction, and the ability to conform to comple…