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相关论文: Research on Navigation Methods Based on LLMs

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Large Language Model (LLM) agents significantly extend the capabilities of standalone LLMs, empowering them to interact with external tools (e.g., APIs, functions) and complete various tasks in a self-directed fashion. The challenge of tool…

人工智能 · 计算机科学 2024-02-19 Weizhou Shen , Chenliang Li , Hongzhan Chen , Ming Yan , Xiaojun Quan , Hehong Chen , Ji Zhang , Fei Huang

The future of autonomous vehicles lies in the convergence of human-centric design and advanced AI capabilities. Autonomous vehicles of the future will not only transport passengers but also interact and adapt to their desires, making the…

人机交互 · 计算机科学 2023-09-20 Can Cui , Yunsheng Ma , Xu Cao , Wenqian Ye , Ziran Wang

Object-Goal Navigation (ObjectNav) requires an agent to find and navigate to a target object category in unknown environments. While recent Large Language Model (LLM)-based agents exhibit zero-shot reasoning, they often rely on a "reactive"…

计算机视觉与模式识别 · 计算机科学 2026-03-10 Yudai Noda , Kanji Tanaka

The increasingly complex and diverse planetary exploration environment requires more adaptable and flexible rover navigation strategy. In this study, we propose a VLM-empowered multi-mode system to achieve efficient while safe autonomous…

机器人学 · 计算机科学 2025-06-23 Sinuo Cheng , Ruyi Zhou , Wenhao Feng , Huaiguang Yang , Haibo Gao , Zongquan Deng , Liang Ding

This paper presents a novel methodological framework for detecting and classifying latent constructs, including frames, narratives, and topics, from textual data using Open-Source Large Language Models (LLMs). The proposed hybrid approach…

计算与语言 · 计算机科学 2025-04-01 Maël Kubli

Modern transportation systems face pressing challenges due to increasing demand, dynamic environments, and heterogeneous information integration. The rapid evolution of Large Language Models (LLMs) offers transformative potential to address…

人工智能 · 计算机科学 2025-06-24 Tong Nie , Jian Sun , Wei Ma

Service robots are increasingly deployed in diverse and dynamic environments, where both physical layouts and social contexts change over time and across locations. In these unstructured settings, conventional navigation systems that rely…

机器人学 · 计算机科学 2025-07-16 Yanbo Wang , Zipeng Fang , Lei Zhao , Weidong Chen

Large Language Models (LLMs) have been employed in financial decision making, enhancing analytical capabilities for investment strategies. Traditional investment strategies often utilize quantitative models, fundamental analysis, and…

综合金融 · 定量金融 2025-07-04 Sedigheh Mahdavi , Jiating , Chen , Pradeep Kumar Joshi , Lina Huertas Guativa , Upmanyu Singh

Autonomous shipping has recently gained much interest in the research community. However, little research focuses on inland - and port navigation, even though this is identified by countries such as Belgium and the Netherlands as an…

Large language models (LLMs) have substantially advanced machine learning research, including natural language processing, computer vision, data mining, etc., yet they still exhibit critical limitations in explainability, reliability,…

机器学习 · 计算机科学 2025-09-19 Xin Wang , Haoyang Li , Haibo Chen , Zeyang Zhang , Wenwu Zhu

Large language models (LLMs) exhibit superior performance on various natural language tasks, but they are susceptible to issues stemming from outdated data and domain-specific limitations. In order to address these challenges, researchers…

计算与语言 · 计算机科学 2024-10-24 Zhangyin Feng , Weitao Ma , Weijiang Yu , Lei Huang , Haotian Wang , Qianglong Chen , Weihua Peng , Xiaocheng Feng , Bing Qin , Ting liu

This work presents an analytical framework for the design and analysis of LLM-based algorithms, i.e., algorithms that contain one or multiple calls of large language models (LLMs) as sub-routines and critically rely on the capabilities of…

机器学习 · 计算机科学 2025-10-14 Yanxi Chen , Yaliang Li , Bolin Ding , Jingren Zhou

Large multimodal models (LMMs) show strong visual-linguistic reasoning but their capacity for spatial decision-making and action remains unclear. In this work, we investigate whether LMMs can achieve embodied spatial action like human…

Large language models (LLMs) have revolutionized natural language processing by achieving state-of-the-art performance across various tasks. Recently, their effectiveness as embedding models has gained attention, marking a paradigm shift…

计算与语言 · 计算机科学 2025-07-28 Chongyang Tao , Tao Shen , Shen Gao , Junshuo Zhang , Zhen Li , Kai Hua , Wenpeng Hu , Zhengwei Tao , Shuai Ma

In autonomous exploration tasks, robots are required to explore and map unknown environments while efficiently planning in dynamic and uncertain conditions. Given the significant variability of environments, human operators often have…

机器人学 · 计算机科学 2025-03-11 Shuhao Liao , Xuxin Lv , Yuhong Cao , Jeric Lew , Wenjun Wu , Guillaume Sartoretti

Recent breakthroughs in large language models (LLMs) have not only advanced natural language processing but also inspired their application in domains with structurally similar problems--most notably, autonomous driving motion generation.…

人工智能 · 计算机科学 2025-09-04 Mingyi Wang , Jingke Wang , Tengju Ye , Junbo Chen , Kaicheng Yu

While large language models (LLMs) are transforming engineering and technology through enhanced control capabilities and decision support, they are simultaneously evolving into complex dynamical systems whose behavior must be regulated.…

系统与控制 · 电气工程与系统科学 2026-05-21 Komeil Nosrati , Aleksei Tepljakov , Juri Belikov , Eduard Petlenkov

Autonomous driving has the potential to set the stage for more efficient future mobility, requiring the research domain to establish trust through safe, reliable and transparent driving. Large Language Models (LLMs) possess reasoning…

机器人学 · 计算机科学 2025-03-06 Katharina Winter , Mark Azer , Fabian B. Flohr

With rapid advances in code generation, reasoning, and problem-solving, Large Language Models (LLMs) are increasingly applied in robotics. Most existing work focuses on high-level tasks such as task decomposition. A few studies have…

机器人学 · 计算机科学 2025-07-29 Zhongchao Zhou , Yuxi Lu , Yaonan Zhu , Yifan Zhao , Bin He , Liang He , Wenwen Yu , Yusuke Iwasawa

Large Language Models (LLMs), originally developed for natural language processing (NLP), have demonstrated the potential to generalize across modalities and domains. With their in-context learning (ICL) capabilities, LLMs can perform…

人工智能 · 计算机科学 2025-08-26 Nikolaos Pavlidis , Vasilis Perifanis , Symeon Symeonidis , Pavlos S. Efraimidis