arXivDaily arXiv每日学术速递 周一至周五更新

期刊&会议

International Conference on Intelligent Robots and Systems · 会议 · Robotics

2026-07-07 至 2026-07-07 共收录 11
2607.05131 2026-07-07 cs.AI 新提交

TacReasoner: A Dynamic Tactile-Language Framework for Interactive Reasoning in Real-World Scenarios

TacReasoner:面向真实场景交互推理的动态触觉-语言框架

Kailin Lyu, Di Wu, Long Xiao, Jianning Zeng, Jianwei He, Chang Lin, Lianyu Hu, Lin Shu, Jie Hao, Ce Hao

机构 * Institute of Automation, Chinese Academy of Sciences(中国科学院自动化研究所) Beijing Zhongguancun Academy(北京中关村科学城) Nanyang Technological University(南洋理工大学) Guangdong Institute of Artificial Intelligence and Advanced Computing(广东省人工智能与先进计算研究院)

AI总结 针对动态触觉信号建模不足、触觉基础模型易幻觉的问题,提出含动态触觉编码器的TacReasoner框架,配套构建TouchCoT-10k数据集与DynTac-Bench基准,推理性能优于主流大模型。

Comments 8 pages, 7 figures. Accepted at IROS 2026

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2607.04879 2026-07-07 cs.RO 新提交

WinTA-GIL: Windowed Trajectory Alignment for GNSS-IMU-LiDAR Heading Refinement in Intermittent Signal Environments

WinTA-GIL:间歇信号环境下用于GNSS-IMU-LiDAR航向精化的窗口轨迹对齐

Kaixin Feng, Zhichao Wen, Zhaohong Liao, Xin Xia, You Li

机构 * State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University(武汉大学测绘遥感信息工程国家重点实验室) School of Remote Sensing and Information Engineering, Wuhan University(武汉大学遥感信息工程学院) College of Engineering and Computer Science, University of Michigan-Dearborn(美国密歇根大学迪尔伯恩分校工程与计算机科学学院)

AI总结 针对多源融合定位系统中航向估计难题,提出WinTA-GIL框架,通过基于时间窗口的优化策略融合GNSS、IMU和LiDAR信息,将航向估计转化为轨迹一致性优化问题,实验证明其性能优越。

Comments Accepted to IROS 2026.8 pages,10 figures

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2607.03758 2026-07-07 cs.RO cs.CR 新提交

Occluding the Solution Space: Planner-Agnostic Adversarial Attacks on Tolerance-Aware Manipulation

遮挡解空间:针对容错感知操纵的与规划器无关的对抗攻击

Keke Tang, Tianyu Hao, Weilong Peng, Hao Jiang, Feng Wu, Peican Zhu, Jianmin Ji, Zhihong Tian

机构 * Guangzhou University(广州大学) University of Science and Technology of China(中国科学技术大学) Northwestern Polytechnical University(西北工业大学)

AI总结 提出针对容错感知操纵的与规划器无关攻击框架,通过运动学占用热图刻画机器人能力,将攻击设为预算最大覆盖优化,实验表明该方法能可靠引发规划失败,优于基线。

Comments Accepted by IROS'2026

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2607.03470 2026-07-07 cs.CV 新提交

PhysMirror: Physics-Aware Mirror Object Generation

物理镜像:物理感知镜像对象生成

Xuan-Bach Mai, Duy-Phuc Nguyen, Quoc-Van Le, Tam V. Nguyen, Thanh-Toan Do, Huu Le, Duong-Van Nguyen, Minh-Triet Tran, Trung-Nghia Le

机构 * University of Science, Ho Chi Minh City(胡志明市科学大学) Vietnam National University, Ho Chi Minh City(胡志明市越南国家大学) University of Dayton(代顿大学) Monash University(莫纳什大学) VinFast(VinFast公司) VinUniversity(Vin大学)

AI总结 针对现代文本到图像扩散模型合成物理精确镜像反射的挑战,提出物理感知生成框架PhysMirror,通过3D空间先验执行投影几何,引入评估指标,实验表明其在反射精度等方面优于基线。

Comments IROS 2026

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2607.03204 2026-07-07 cs.RO 新提交

Layout-independent actuation allocator for fin-actuated marine robots

用于鳍驱动海洋机器人的与布局无关的驱动分配器

Yuya Hamamatsu, Maarja Kruusmaa, Asko Ristolainen

机构 * Department of Computer Systems, Tallinn University of Technology(计算机系统系,塔林理工大学)

AI总结 研究提出与布局无关的控制分配器,用含图神经网络、Transformer和混合密度网络的学习管道及可微物理代理模型,实现跨不同执行器配置零样本部署,提升轨迹跟踪性能。

Comments Accepted by 2026 International Conference on Intelligent Robots and Systems (IROS)

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2607.03072 2026-07-07 cs.MA cs.RO 新提交

LOTUSim: Multi-Domain Simulator for Marine Robotics

LOTUSim:海洋机器人多域模拟器

Cédric Buche, Juliette Grosset, Hélène Lechêne, Marie Dubromel, Pierig Havez-Bodivit, Malcom Neo, Julien Prodhon

机构 * CROSSING IRL 2010, CNRS(CROSSING IRL 2010,CNRS) Naval Group, France(法国海军集团) IMT Atlantique(IMT阿蒂旺)

AI总结 介绍LOTUSim多域海洋模拟器,其贡献一是支持多用户跨系统交互,确保实时性与可扩展性;二是有高效水下电流模型,验证显示相比常用模型精度大幅提升,适合海洋机器人研究。

Journal ref 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IROS, Sep 2026, Pittsburgh (Etats-Unis), United States

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2606.28720 2026-07-07 cs.RO 版本更新

CubifyGS: Object-Centric 3D Gaussian Splatting for Lifelong Dynamic Scene Maintenance

CubifyGS: 面向对象的3D高斯泼溅用于终身动态场景维护

Bohan Ren, Dianyi Yang, Shiyang Liu, Yu Gao, Jiadong Tang, Zhilin Lai, Yi Yang, Mengyin Fu

机构 * School of Automation, Beijing Institute of Technology, Beijing, China(北京理工大学自动化学院,北京,中国) Guangzhou Saite Intelligent Technology Co., Ltd.(广州赛泰智能科技有限公司)

AI总结 提出CubifyGS,一种面向对象的映射框架,通过将可移动实例建模为可重用高斯资产,并采用事件触发自适应优化,实现刚性物体重排下的高效动态场景维护。

Comments Accepted to IROS 2026. 8 pages, 5 figures, 4 tables

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2604.21241 2026-07-07 cs.RO cs.AI 版本更新

CorridorVLA: Explicit Spatial Constraints for Generative Action Heads via Sparse Anchors

CorridorVLA:通过稀疏锚点实现生成动作头的显式空间约束

Dachong Li, ZhuangZhuang Chen, Jin Zhang, Jianqiang Li

机构 * College of Computer Science and Software Engineering(计算机科学与软件工程学院) National Engineering Laboratory for Big Data System Computing Technology(大数据系统计算技术国家工程实验室)

AI总结 CorridorVLA通过稀疏锚点提供显式空间约束,提升动作生成性能,在LIBERO-Plus基准上改进成功率3.4%-12.4%。

Comments Accepted to the 2026 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2026)

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2603.20659 2026-07-07 cs.RO 版本更新

StageCraft: Execution Aware Mitigation of Distractor and Obstruction Failures in VLA Models

StageCraft: 通过执行意识缓解VLA模型中干扰和障碍故障

Kartikay Milind Pangaonkar, Prabin Rath, Omkar Patil, Nakul Gopalan

机构 * Arizona State University(亚利桑那州立大学)

AI总结 StageCraft通过利用大规模视觉语言模型进行推理,改进预训练VLA策略性能,通过操控环境初始状态避免执行故障,实现在三个真实任务领域中性能提升40%。

Comments Accepted to IEEE International Conference on Intelligent Robots and Systems (IROS) 2026

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2409.10733 2026-07-07 cs.RO cs.LG

BaTCAVe: Trustworthy Explanations for Robot Behaviors

BaTCAVe:机器人行为的可信解释

Som Sagar, Aditya Taparia, Harsh Mankodiya, Pranav Bidare, Yifan Zhou, Ransalu Senanayake

机构 * School of Computing and Augmented Intelligence, Arizona State University(计算与增强智能学院,亚利桑那州立大学)

AI总结 本文提出基于人类可理解的高层概念的可信可解释机器人技术,通过匹配神经网络激活与可视化来提供带有不确定性评分的解释,验证了其作为事后人类友好的机器人诊断工具的有效性。

Comments 19 pages, 26 figures

Journal ref 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hangzhou, China, 2025, pp. 13867-13874

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2509.15061 2026-07-07 cs.RO cs.CV 版本更新

Ask-to-Clarify: Resolving Instruction Ambiguity through Multi-turn Dialogue

Ask-to-Clarify: 通过多轮对话解决指令歧义

Xingyao Lin, Xinghao Zhu, Tianyi Lu, Guojin Zhong, Sicheng Xie, Hui Zhang, Xipeng Qiu, Zuxuan Wu, Yu-Gang Jiang

机构 * College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China(复旦大学计算机科学与人工智能学院) Shanghai Innovation Institute, Shanghai, China(上海创新研究院) Mechanical Systems Control Lab, UC Berkeley, California, USA(伯克利机械系统控制实验室)

AI总结 本文提出Ask-to-Clarify框架,通过多轮对话解决指令歧义问题,结合视觉语言模型和扩散模型,采用两阶段知识绝缘策略训练,实现多任务中更高效的协作式具身代理。

Comments Accepted by IROS 2026

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