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With the increasing use of drones across various industries, the navigation and tracking of these unmanned aerial vehicles (UAVs) in challenging environments (such as GNSS-denied environments) have become critical issues. In this paper, we…

机器人学 · 计算机科学 2023-07-19 Iacopo Catalano , Ha Sier , Xianjia Yu , Tomi Westerlund , Jorge Pena Queralta

With the advancement of maritime unmanned aerial vehicles (UAVs) and deep learning technologies, the application of UAV-based object detection has become increasingly significant in the fields of maritime industry and ocean engineering.…

计算机视觉与模式识别 · 计算机科学 2023-11-16 Chenjie Zhao , Ryan Wen Liu , Jingxiang Qu , Ruobin Gao

Navigating unmanned aerial vehicles (UAVs) through cluttered and dynamic environments remains a significant challenge, particularly when dealing with fast-moving or sudden-appearing obstacles. This paper introduces a complete LiDAR-based…

机器人学 · 计算机科学 2025-04-25 Huajie Wu , Wenyi Liu , Yunfan Ren , Zheng Liu , Hairuo Wei , Fangcheng Zhu , Haotian Li , Fu Zhang

With the increasing prevalence of drones in various industries, the navigation and tracking of unmanned aerial vehicles (UAVs) in challenging environments, particularly GNSS-denied areas, have become crucial concerns. To address this need,…

机器人学 · 计算机科学 2023-10-16 Iacopo Catalano , Xianjia Yu , Jorge Pena Queralta

This paper presents a novel approach to build consistent 3D maps for multi robot cooperation in USAR environments. The sensor streams from unmanned aerial vehicles (UAVs) and ground robots (UGV) are fused in one consistent map. The UAV…

机器人学 · 计算机科学 2019-04-10 Hartmut Surmann , Nils Berninger , Rainer Worst

Robust object detection for Unmanned Surface Vehicles (USVs) in complex water environments is essential for reliable navigation and operation. Specifically, water surface object detection faces challenges from blurred edges and diverse…

计算机视觉与模式识别 · 计算机科学 2025-04-11 Huilin Yin , Pengyu Wang , Senmao Li , Jun Yan , Daniel Watzenig

Compact UAV systems, while advancing delivery and surveillance, pose significant security challenges due to their small size, which hinders detection by traditional methods. This paper presents a cost-effective, unsupervised UAV detection…

计算机视觉与模式识别 · 计算机科学 2025-01-22 Hanfang Liang , Yizhuo Yang , Jinming Hu , Jianfei Yang , Fen Liu , Shenghai Yuan

For an autonomous surface vessel (ASV) to dock, it must track other vessels close to the docking area. Kayaks present a particular challenge due to their proximity to the dock and relatively small size. Maritime target tracking has…

计算机视觉与模式识别 · 计算机科学 2025-02-26 Nicholas Dalhaug , Annette Stahl , Rudolf Mester , Edmund Førland Brekke

The vision of unmanned aerial vehicles is very significant for UAV-related applications such as search and rescue, landing on a moving platform, etc. In this work, we have developed an integrated system for the UAV landing on the moving…

机器人学 · 计算机科学 2023-01-03 Kangcheng Liu

Research on coastal regions traditionally involves methods like manual sampling, monitoring buoys, and remote sensing, but these methods face challenges in spatially and temporally diverse regions of interest. Autonomous surface vehicles…

机器人学 · 计算机科学 2024-05-29 Mingi Jeong

Deploying autonomous robots in crowded indoor environments usually requires them to have accurate dynamic obstacle perception. Although plenty of previous works in the autonomous driving field have investigated the 3D object detection…

机器人学 · 计算机科学 2024-02-28 Zhefan Xu , Xiaoyang Zhan , Yumeng Xiu , Christopher Suzuki , Kenji Shimada

In the maritime sector, safe vessel navigation is of great importance, particularly in congested harbors and waterways. The focus of this work is to estimate the distance between an object of interest and potential obstacles using a…

机器人学 · 计算机科学 2021-08-10 Jonas le Fevre Sejersen , Rui Pimentel de Figueiredo , Erdal Kayacan

An accurate and rapid-response perception system is fundamental for autonomous vehicles to operate safely. 3D object detection methods handle point clouds given by LiDAR sensors to provide accurate depth and position information for each…

机器人学 · 计算机科学 2020-08-04 Guidong Yang , Simone Mentasti , Mattia Bersani , Yafei Wang , Francesco Braghin , Federico Cheli

Reliable obstacle detection and classification in rough and unstructured terrain such as agricultural fields or orchards remains a challenging problem. These environments involve large variations in both geometry and appearance, challenging…

机器人学 · 计算机科学 2019-03-14 Mikkel Kragh , James Underwood

Large driving datasets are a key component in the current development and safeguarding of automated driving functions. Various methods can be used to collect such driving data records. In addition to the use of sensor equipped research…

计算机视觉与模式识别 · 计算机科学 2020-06-23 Laurent Kloeker , Christian Geller , Amarin Kloeker , Lutz Eckstein

Lidar-based sensing drives current autonomous vehicles. Despite rapid progress, current Lidar sensors still lag two decades behind traditional color cameras in terms of resolution and cost. For autonomous driving, this means that large…

计算机视觉与模式识别 · 计算机科学 2021-11-15 Tianwei Yin , Xingyi Zhou , Philipp Krähenbühl

- Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions.…

机器人学 · 计算机科学 2019-07-02 Hatem Hajri , Mohamed-Cherif Rahal

A novel approach for robust state estimation of marine vessels in rough water is proposed in this paper to enable tight collaboration between Unmanned Aerial Vehicles (UAVs) and a marine vessel, such as cooperative landing or object…

机器人学 · 计算机科学 2025-02-19 Filip Novák , Tomáš Báča , Ondřej Procházka , Martin Saska

Avoiding hybrid obstacles in unknown scenarios with an efficient flight strategy is a key challenge for unmanned aerial vehicle applications. In this paper, we introduce a technique to distinguish dynamic obstacles from static ones with…

机器人学 · 计算机科学 2021-05-17 Han Chen , Peng Lu

Localization, or position fixing, is an important problem in robotics research. In this paper, we propose a novel approach for long-term localization in a changing environment using 3D LiDAR. We first create the map of a real environment…

机器人学 · 计算机科学 2019-10-29 Yilong Zhu , Bohuan Xue , Linwei Zheng , Huaiyang Huang , Ming Liu , Rui Fan