机器人框架GSAM增强了铰接式物体操作能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-01 04:00

研究人员开发了GSAM，一个旨在改进铰接式物体操作的新机器人框架。该系统使用基于视觉的感知器和经过微调的、具有链式思考推理能力的VLM来优化物体感知。GSAM还包含一个交互约束函数生成器和一个用于轨迹规划的LLM，旨在防止碰撞并增强在各种物体类型和交互场景中的泛化能力。 AI

影响该框架可以提高机器人在复杂操作任务中的灵活性和安全性，有可能加速其在服务行业的部署。

排序理由该集群包含一篇详细介绍新型机器人操作框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Beichen Shao, Mengying Xie, Heng Su, Wanyi Zhang, Mingyan Li, Yan Ding, Fausto Giunchiglia, Chao Chen · 2026-06-01 04:00

GSAM：一种可泛化且安全的机器人框架，用于操作铰接式物体

arXiv:2605.30740v1 Announce Type: cross Abstract: Articulated object manipulation is a unique challenge for service robots. Existing methods employ end-to-end policy learning, visionmotion planning, and large-language/visual-language model (LLM/VLM), but often overlook the divers…