5 papers · 1 filter
AGM: Achievement-Grounded Memory for Closed-Loop Agents with Frozen VLA Policies
Hongbo Gao, Zeyu Ni, Xin Wen +4
Frozen vision-language-action (VLA) policies offer broad manipulation skills but execute open-loop action chunks without tracking task progress, so the agent cannot reliably decide…
FoMoVLA: Bridging Visual Foresight and Motion Guidance for Vision-Language-Action Models
Wei Li, Peijin Jia, Yuan Ma +9
Vision-Language-Action (VLA) models have achieved impressive results in visuomotor policy learning, yet remain fundamentally reactive, mapping current observations and language to…
ComSim: Building Scalable Real-World Robot Data Generation via Compositional Simulation
Yiran Qin, Jiahua Ma, Li Kang +11
Recent advancements in foundational models, such as large language models and world models, have greatly enhanced the capabilities of robotics, enabling robots to autonomously perf…
Referring-Aware Visuomotor Policy Learning for Closed-Loop Manipulation
Jiahua Ma, Yiran Qin, Xin Wen +5
This paper addresses a fundamental problem of visuomotor policy learning for robotic manipulation: how to enhance robustness in out-of-distribution execution errors or dynamically…
TouchGuide: Inference-Time Steering of Visuomotor Policies via Touch Guidance
Zhemeng Zhang, Jiahua Ma, Xincheng Yang +13
Fine-grained and contact-rich manipulation remain challenging for robots, largely due to the underutilization of tactile feedback. To address this, we introduce TouchGuide, a novel…