The ability to navigate like a human towards a language-guided target from anywhere in a 3D embodied environment is one of the 'holy grail' goals of intelligent robots. Most visual navigation benchmarks, however, focus on navigating toward a target from a fixed starting point, guided by an elaborate set of instructions that depicts step-by-step. This approach deviates from real-world problems in which human-only describes what the object and its surrounding look like and asks the robot to start navigation from anywhere. Accordingly, in this paper, we introduce a Scenario Oriented Object Navigation (SOON) task. In this task, an agent is required to navigate from an arbitrary position in a 3D embodied environment to localize a target following a scene description. To give a promising direction to solve this task, we propose a novel graph-based exploration (GBE) method, which models the navigation state as a graph and introduces a novel graph-based exploration approach to learn knowledge from the graph and stabilize training by learning sub-optimal trajectories. We also propose a new large-scale benchmark named From Anywhere to Object (FAO) dataset. To avoid target ambiguity, the descriptions in FAO provide rich semantic scene information includes: object attribute, object relationship, region description, and nearby region description. Our experiments reveal that the proposed GBE outperforms various state-of-the-arts on both FAO and R2R datasets. And the ablation studies on FAO validates the quality of the dataset.
MUSON: A Reasoning-oriented Multimodal Dataset for Socially Compliant Navigation in Urban Environments
Graduate School of Information Science and Technology, Hokkaido University（北海道大学信息科学研究生院）；Graduate School of Computer Science, George Mason University（乔治·马歇尔大学计算机科学研究生院）
Learning Goal-Oriented Vision-and-Language Navigation with Self-Improving Demonstrations at Scale
Shanghai AI Laboratory（上海人工智能实验室）；UNC Chapel Hill（北卡罗来纳大学教堂山分校）；Fudan University（复旦大学）；The University of Adelaide（阿德莱德大学）；Nanjing University（南京大学）；Shanghai Jiaotong University（上海交通大学）
Beyond Spatial Benchmarks: From Spatial Reasoning to Navigation
Xiamen University（厦门大学）；Zhongguancun Academy（中关村学院）；Beihang University（北京航空航天大学）；Beijing Institute of Technology（北京理工大学）；University of Chinese Academy of Sciences（中国科学院大学）
Towards Realistic UAV Vision-Language Navigation: Platform, Benchmark, and Methodology
Institute of Artificial Intelligence, Beihang University（北京航空航天大学人工智能学院）；MMLab, CUHK（香港中文大学MMLab）；Centre for Perceptual and Interactive Intelligence（感知与交互智能中心）
TONAV: Task-Oriented Navigation and Action-Velocity Chunk Learning for Articulated Object Quadrupedal Mobile Manipulation
School of Artificial Intelligence and Robotics, Hunan University（湖南大学人工智能与机器人学院）；National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University（湖南大学机器人视觉感知与控制技术国家工程研究中心）；College of Semiconductors (College of Integrated Circuits), Hunan University（湖南大学半导体学院（集成电路学院））
Temporal-Spatial Object Relations Modeling for Vision-and-Language Navigation
School of Computer Science and Technology, Institute of Intelligent Computing, Shandong University（山东大学计算机科学与技术学院智能计算研究所）；City University of Hong Kong（香港城市大学）
Disrupting Vision-Language Model-Driven Navigation Services via Adversarial Object Fusion
College of Computer Science, Chongqing University（重庆大学计算机学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算机与数据科学学院）；School of Computer Science and Technology, Xidian University（西安电子科技大学计算机科学与技术学院）
RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied Navigation
MBZUAI（默罕默德·本·扎耶德人工智能大学）；Shenzhen Campus of Sun Yat-Sen University（中山大学深圳校区）；AAII, UTS（悉尼科技大学人工智能与创新研究所）；University of Science and Technology of China（中国科学技术大学）
Implicit Geometry Representations for Vision-and-Language Navigation from Web Videos
Department of Computer Vision, Mohamed Bin Zayed University of Artificial Intelligence（计算机视觉系，Mohamed Bin Zayed人工智能大学）；School of Information Science and Technology, University of Science and Technology of China（信息科学与技术学院，中国科学技术大学）；Shenzhen Campus of Sun Yat-Sen University（中山大学深圳校区）
Object Memory Transformer for Object Goal Navigation
National Institute of Advanced Industrial Science and Technology (AIST)（日本产业技术综合研究所（AIST））；Tokyo Institute of Technology（东京工业大学）；Mitsubishi Electric Corporation（三菱电机公司）
