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期刊&会议

IEEE RA-L

IEEE Robotics and Automation Letters · 期刊 · Robotics

2026-01-06 至 2026-01-06 共收录 3
2601.01872 2026-01-06 cs.RO

CausalNav: A Long-term Embodied Navigation System for Autonomous Mobile Robots in Dynamic Outdoor Scenarios

CausalNav: 一种面向动态户外场景的自主移动机器人长期具身导航系统

Hongbo Duan, Shangyi Luo, Zhiyuan Deng, Yanbo Chen, Yuanhao Chiang, Yi Liu, Fangming Liu, Xueqian Wang

机构 * Center for Artificial Intelligence and Robotics, Shenzhen International Graduate School, Tsinghua University(人工智能与机器人中心,深圳国际研究生院,清华大学) Peng Cheng Laboratory(鹏城实验室)

AI总结 CausalNav是一种基于场景图的语义导航框架,通过构建多级语义场景图实现动态户外环境中的稳健导航与远距离规划。

Comments Accepted by IEEE Robotics and Automation Letters (RA-L)

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2601.01675 2026-01-06 cs.RO

VisuoTactile 6D Pose Estimation of an In-Hand Object using Vision and Tactile Sensor Data

利用视觉和触觉传感器数据进行手持物体的6D位姿估计

Snehal s. Dikhale, Karankumar Patel, Daksh Dhingra, Itoshi Naramura, Akinobu Hayashi, Soshi Iba, Nawid Jamali

机构 * Honda Research Institute USA, Inc.(本田美国研究院) Honda R&D Co., Ltd.(本田研发公司) Department of Mechanical Engineering, University of Washington(华盛顿大学机械工程系)

AI总结 本文提出利用视觉和触觉数据融合方法,提高机器人在手物体的6D位姿估计精度。

Comments Accepted for publication in IEEE Robotics and Automation Letters (RA-L), January 2022. Presented at ICRA 2022. This is the author's version of the manuscript

Journal ref IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 2228-2235, April 2022

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2505.23019 2026-01-06 cs.RO

Stairway to Success: An Online Floor-Aware Zero-Shot Object-Goal Navigation Framework via LLM-Driven Coarse-to-Fine Exploration

通往成功的阶梯:一种通过LLM驱动的粗到细探索的在线楼层感知零样本物体-目标导航框架

Zeying Gong, Rong Li, Tianshuai Hu, Ronghe Qiu, Lingdong Kong, Lingfeng Zhang, Guoyang Zhao, Yiyi Ding, Junwei Liang

机构 * The Hong Kong University of Science and Technology (Guangzhou)(香港科学与技术大学(广州)) The Hong Kong University of Science and Technology(香港科学与技术大学) National University of Singapore(新加坡国立大学) Tsinghua University(清华大学)

AI总结 本文提出ASCENT框架,通过LLM驱动的粗到细探索实现在线楼层感知零样本物体-目标导航,无需预建地图或重新训练,适用于多楼层环境。

Comments Accepted to IEEE Robotics and Automation Letters (RAL). Project Page at https://zeying-gong.github.io/projects/ascent

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