activity
20192026
most citedMap++: Towards User-Participatory Visual SLAM Systems with Efficient Map Expansion and Sharing

11 citations · 20 across the 27 of their papers we have counts for

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16 papers · 1 filter

cs.RO2026

DriftingVLA: Native One-Step Vision-Language-Action Generation via Per-Dimension Temporal Drifting

Yuxuan Gao, Shiqi Zhang, Yedong Shen +6

Conventional flow-based vision-language-action (VLA) models support expressive continuous action generation but rely on multi-step refinement to produce each action chunk, increasi…

cs.RO2026

DynaHMRC: Decentralized Heterogeneous Multi-Robot Collaboration for Dynamic Tasks with Large Language Models

Wenhao Yu, Yu'ang Xie, Yifan Duan +5

Large language models (LLMs) provide robots with richer task understanding and adaptability, making them promising for coordinating heterogeneous multi-robot systems in long-horizo…

cs.RO2026

Drift-Based Policy Optimization: Native One-Step Policy Learning for Online Robot Control

Yuxuan Gao, Yedong Shen, Shiqi Zhang +6

Diffusion policies effectively model multimodal action distributions for robotic manipulation, but their iterative denoising requires tens to hundreds of network function evaluatio…

cs.RO2026

FAVLA: A Force-Adaptive Fast-Slow VLA model for Contact-Rich Robotic Manipulation

Yao Li, Peiyuan Tang, Wuyang Zhang +7

Force/torque feedback can substantially improve Vision-Language-Action (VLA) models on contact-rich manipulation, but most existing approaches fuse all modalities at a single opera…

cs.RO2025

STDArm: Transferring Visuomotor Policies From Static Data Training to Dynamic Robot Manipulation

Yifan Duan, Heng Li, Yilong Wu +5

Recent advances in mobile robotic platforms like quadruped robots and drones have spurred a demand for deploying visuomotor policies in increasingly dynamic environments. However,…

cs.RO2025

MT-PCR: Leveraging Modality Transformation for Large-Scale Point Cloud Registration with Limited Overlap

Yilong Wu, Yifan Duan, Yuxi Chen +5

Large-scale scene point cloud registration with limited overlap is a challenging task due to computational load and constrained data acquisition. To tackle these issues, we propose…