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相关论文: Drone Detection Using Depth Maps

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Autonomous indoor navigation of UAVs presents numerous challenges, primarily due to the limited precision of GPS in enclosed environments. Additionally, UAVs' limited capacity to carry heavy or power-intensive sensors, such as overheight…

机器人学 · 计算机科学 2024-12-25 Kangtong Mo , Linyue Chu , Xingyu Zhang , Xiran Su , Yang Qian , Yining Ou , Wian Pretorius

This paper presents our method for enabling a UAV quadrotor, equipped with a monocular camera, to autonomously avoid collisions with obstacles in unstructured and unknown indoor environments. When compared to obstacle avoidance in ground…

机器人学 · 计算机科学 2019-11-20 Abhik Singla , Sindhu Padakandla , Shalabh Bhatnagar

UAVs, commonly referred to as drones, have witnessed a remarkable surge in popularity due to their versatile applications. These cyber-physical systems depend on multiple sensor inputs, such as cameras, GPS receivers, accelerometers, and…

软件工程 · 计算机科学 2025-10-21 Ivan Tan , Wei Minn , Christopher M. Poskitt , Lwin Khin Shar , Lingxiao Jiang

The forthcoming era of massive drone delivery deployment in urban environments raises a need to develop reliable control and monitoring systems. While active solutions, i.e., wireless sharing of a real-time location between air traffic…

Drone-captured images present significant challenges in object detection due to varying shooting conditions, which can alter object appearance and shape. Factors such as drone altitude, angle, and weather cause these variations, influencing…

计算机视觉与模式识别 · 计算机科学 2024-11-15 Chanyeong Park , Heegwang Kim , Joonki Paik

Today, low-altitude fixed-wing Unmanned Aerial Vehicles (UAVs) are largely limited to primitively follow user-defined waypoints. To allow fully-autonomous remote missions in complex environments, real-time environment-aware navigation is…

机器人学 · 计算机科学 2017-12-12 Philipp Oettershagen , Florian Achermann , Benjamin Müller , Daniel Schneider , Roland Siegwart

Nowadays there is a growing research interest on the possibility of enriching small flying robots with autonomous sensing and online navigation capabilities. This will enable a large number of applications spanning from remote surveillance…

信息论 · 计算机科学 2020-07-23 Anna Guerra , Davide Dardari , Petar M. Djuric

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

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 more robust technique to distinguish and track dynamic obstacles…

机器人学 · 计算机科学 2021-10-22 Han Chen , Peng Lu

In this paper, we propose a resource-efficient approach to provide an autonomous UAV with an on-board perception method to detect safe, hazard-free landing sites during flights over complex 3D terrain. We aggregate 3D measurements acquired…

Over the last decade, the use of autonomous drone systems for surveying, search and rescue, or last-mile delivery has increased exponentially. With the rise of these applications comes the need for highly robust, safety-critical algorithms…

Object detection from images captured by Unmanned Aerial Vehicles (UAVs) is becoming increasingly useful. Despite the great success of the generic object detection methods trained on ground-to-ground images, a huge performance drop is…

计算机视觉与模式识别 · 计算机科学 2020-10-06 Zhenyu Wu , Karthik Suresh , Priya Narayanan , Hongyu Xu , Heesung Kwon , Zhangyang Wang

Estimating the pose of an unmanned aerial vehicle (UAV) or drone is a challenging task. It is useful for many applications such as navigation, surveillance, tracking objects on the ground, and 3D reconstruction. In this work, we present a…

机器人学 · 计算机科学 2020-11-18 Jan Hausberg , Ryoichi Ishikawa , Menandro Roxas , Takeshi Oishi

The widespread use of consumer drones has introduced serious challenges for airspace security and public safety. Their high agility and unpredictable motion make drones difficult to track and intercept. While existing methods focus on…

机器人学 · 计算机科学 2025-07-08 Hanfang Liang , Shenghai Yuan , Fen Liu , Yizhuo Yang , Bing Wang , Zhuyu Huang , Chenyang Shi , Jing Jin

In this paper, a deep reinforcement learning (DRL) method is proposed to address the problem of UAV navigation in an unknown environment. However, DRL algorithms are limited by the data efficiency problem as they typically require a huge…

机器人学 · 计算机科学 2020-08-07 Lei He , Nabil Aouf , James F. Whidborne , Bifeng Song

Drone-based rapid and accurate environmental edge detection is highly advantageous for tasks such as disaster relief and autonomous navigation. Current methods, using radars or cameras, raise deployment costs and burden lightweight drones…

This work aims to investigate the use of deep neural network to detect commercial hobby drones in real-life environments by analyzing their sound data. The purpose of work is to contribute to a system for detecting drones used for malicious…

声音 · 计算机科学 2017-01-23 Sungho Jeon , Jong-Woo Shin , Young-Jun Lee , Woong-Hee Kim , YoungHyoun Kwon , Hae-Yong Yang

Unmanned Aerial Vehicles (UAVs) are known for their fast and versatile applicability. With UAVs' growth in availability and applications, they are now of vital importance in serving as technological support in search-and-rescue(SAR)…

计算机视觉与模式识别 · 计算机科学 2024-09-18 Xiaomin Lin , Cheng Liu , Allen Pattillo , Miao Yu , Yiannis Aloimonous

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

Autonomous deployment of unmanned aerial vehicles (UAVs) supporting next-generation communication networks requires efficient trajectory planning methods. We propose a new end-to-end reinforcement learning (RL) approach to UAV-enabled data…

机器学习 · 计算机科学 2021-01-28 Harald Bayerlein , Mirco Theile , Marco Caccamo , David Gesbert