An algorithm for pose and motion estimation using corresponding features in images and a digital terrain map is proposed. Using a Digital Terrain (or Digital Elevation) Map (DTM/DEM) as a global reference enables recovering the absolute position and orientation of the camera. In order to do this, the DTM is used to formulate a constraint between corresponding features in two consecutive frames. The utilization of data is shown to improve the robustness and accuracy of the inertial navigation algorithm. Extended Kalman filter was used to combine results of inertial navigation algorithm and proposed vision-based navigation algorithm. The feasibility of this algorithms is established through numerical simulations.
Utilizing High-level Visual Feature for Indoor Shopping Mall Navigation
University of Science and Technology of China（中国科学技术大学）；Hong Kong University of Science and Technology（香港科技大学）；Dajiang Innovations Co., Ltd.（大疆创新科技有限公司）
Predicting Dense and Context-aware Cost Maps for Semantic Robot Navigation
University of Bonn（波恩大学）；Robert Bosch GmbH（罗伯特·博世有限公司）；University of Oxford（牛津大学）；Lamarr Institute for Machine Learning and Artificial Intelligence（拉马尔机器学习与人工智能研究所）
Dynamic Topology Awareness: Breaking the Granularity Rigidity in Vision-Language Navigation
Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院航空航天信息研究所）；School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences（中国科学院大学电子电气与通信工程学院）；Department of Computer Science, City University of Hong Kong（香港城市大学计算机科学系）
NavMapFusion: Diffusion-based Fusion of Navigation Maps for Online Vectorized HD Map Construction
Mercedes-Benz Research & Development North America, USA（梅赛德斯-奔驰北美研究与开发）；University of Stuttgart, Germany（斯图加特大学）；University of California, San Diego, USA（加州大学圣地亚哥分校）；University of Southampton, United Kingdom（南安普顿大学）
RoadRunner -- Learning Traversability Estimation for Autonomous Off-road Driving
Jet Propulsion Laboratory (JPL)（喷气推进实验室）；California Institute of Technology (Caltech)（加州理工学院）；Swiss Federal Institute of Technology (ETH Zürich)（苏黎世联邦理工学院）
Robust and accurate depth estimation by fusing LiDAR and Stereo
University of the Chinese Academy of Sciences（中国科学院大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Electric Power Research Institute, State Grid Shandong Electric Power Company（国网山东省电力公司电力科学研究院）
WaterVG: Waterway Visual Grounding based on Text-Guided Vision and mmWave Radar
Institute of Deep Perception Tech, JITRI（JITRI深度感知技术研究所）；School of Advanced Technology, Xi’an Jiaotong-Liverpool University（西交利物浦大学先进技术学院）；Faculty of Science and Engineering, University of Liverpool（利物浦大学科学与工程学院）；Thrust of Artificial Intelligence and Thrust of Intelligent Transportation, HKUST (Guangzhou)（香港科技大学（广州）人工智能学科及智能交通学科）
