6 papers · 1 filter
FlowDAgger: Human-in-the-Loop Adaptation of Generative Robot Policies in Latent Space
Michael Murray, Daphne Chen, Simran Bagaria +7
Pretrained generative robot policies based on flow matching and diffusion have achieved impressive results across a wide range of manipulation tasks. Yet real-world deployments rou…
Offload or Overload: A Platform Measurement Study of Mobile Robotic Manipulation Workloads
Sara Pohland, Xenofon Foukas, Ganesh Ananthanarayanan +4
Mobile robotic manipulation--the ability of robots to navigate spaces and interact with objects--is a core capability of physical AI. Foundation models have led to breakthroughs in…
TwinVLA: Data-Efficient Bimanual Manipulation with Twin Single-Arm Vision-Language-Action Models
Hokyun Im, Euijin Jeong, Andrey Kolobov +2
Vision-language-action models (VLAs) trained on large-scale robotic datasets have demonstrated strong performance on manipulation tasks, including bimanual tasks. However, because…
Benchmarking Affordance Generalization with BusyBox
Dean Fortier, Timothy Adamson, Tess Hellebrekers +5
Vision-Language-Action (VLA) models have been attracting the attention of researchers and practitioners thanks to their promise of generalization. Although single-task policies sti…
LoLA: Long Horizon Latent Action Learning for General Robot Manipulation
Xiaofan Wang, Xingyu Gao, Jianlong Fu +5
The capability of performing long-horizon, language-guided robotic manipulation tasks critically relies on leveraging historical information and generating coherent action sequence…
TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies
Ruijie Zheng, Yongyuan Liang, Shuaiyi Huang +5
Although large vision-language-action (VLA) models pretrained on extensive robot datasets offer promising generalist policies for robotic learning, they still struggle with spatial…