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Autonomous aerial-surface robot teams offer a scalable solution for maritime monitoring, but deployment remains difficult due to water-induced visual artifacts and bandwidth-limited coordination. This paper presents a decentralized…

机器人学 · 计算机科学 2026-03-03 Muhammad Farhan Ahmed , Vincent Frémont

Accurate mapping of individual trees is essential for ecological monitoring and forest management. Orthomosaic imagery from unmanned aerial vehicles (UAVs) is widely used, but stitching artifacts and heavy preprocessing limit its…

Enabling autonomous robots to safely and efficiently navigate, explore, and map underwater caves is of significant importance to water resource management, hydrogeology, archaeology, and marine robotics. In this work, we demonstrate the…

机器人学 · 计算机科学 2025-04-25 Alankrit Gupta , Adnan Abdullah , Xianyao Li , Vaishnav Ramesh , Ioannis Rekleitis , Md Jahidul Islam

Aerial cinematography is revolutionizing industries that require live and dynamic camera viewpoints such as entertainment, sports, and security. However, safely piloting a drone while filming a moving target in the presence of obstacles is…

The advancement of agricultural robotics holds immense promise for transforming fruit harvesting practices, particularly within the apple industry. The accurate detection and localization of fruits are pivotal for the successful…

计算机视觉与模式识别 · 计算机科学 2024-05-13 Jiang Ziyue , Yin Bo , Lu Boyun

The objective of this work is to develop a data processing system that can automatically generate waypoints for navigation of an unmanned aerial vehicle (UAV) to inspect surfaces of structures like buildings and bridges. The input includes…

机器人学 · 计算机科学 2017-02-14 M. D. Phung , C. H. Quach , D. T. Chu , N. Q. Nguyen , T. H. Dinh , Q. P. Ha

Over-the-air computation (AirComp) seamlessly integrates communication and computation by exploiting the waveform superposition property of multiple-access channels. Different from the existing works that focus on transceiver design of…

信号处理 · 电气工程与系统科学 2021-06-02 Min Fu , Yong Zhou , Yuanming Shi , Wei Chen , Rui Zhang

Increased growth in the global Unmanned Aerial Vehicles (UAV) (drone) industry has expanded possibilities for fully autonomous UAV applications. A particular application which has in part motivated this research is the use of UAV in wide…

In precision crop protection, (target-orientated) object detection in image processing can help navigate Unmanned Aerial Vehicles (UAV, crop protection drones) to the right place to apply the pesticide. Unnecessary application of non-target…

计算机视觉与模式识别 · 计算机科学 2021-03-09 Zhenwang Qin , Wensheng Wang , Karl-Heinz Dammer , Leifeng Guo , Zhen Cao

Modern agricultural applications require knowledge about the position and size of fruits on plants. However, occlusions from leaves typically make obtaining this information difficult. We present a novel viewpoint planning approach that…

机器人学 · 计算机科学 2021-08-19 Tobias Zaenker , Claus Smitt , Chris McCool , Maren Bennewitz

The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the…

机器人学 · 计算机科学 2026-03-24 Ebasa Temesgen , Nathnael Minyelshowa , Lebsework Negash

The use of an efficient coverage planning method is key for autonomous navigation in agricultural environments, where a robot must cover large areas of crops. This paper generally reviews the current state of the art of coverage path…

机器人学 · 计算机科学 2024-07-03 Ismael Ait , Ernesto Kofman , Taihú Pire

Aerial insects can effortlessly navigate dense vegetation, whereas similarly sized aerial robots typically depend on offboard sensors and computation to maintain stable flight. This disparity restricts insect-scale robots to operation…

Autonomous robots are used as the tool to solve many kinds of problems, such as environmental mapping and monitoring. Either for adverse conditions related to the human presence or even for the need to reduce costs, it is certain that many…

机器人学 · 计算机科学 2017-10-19 Michel Conrado Cardoso Meneses

Biodiversity loss poses a significant threat to humanity, making wildlife monitoring essential for assessing ecosystem health. Avian species are ideal subjects for this due to their popularity and the ease of identifying them through their…

机器学习 · 计算机科学 2026-02-23 Nina Brolich , Simon Geis , Maximilian Kasper , Alexander Barnhill , Axel Plinge , Dominik Seuß

The paper is concerned with the dynamic tracking problem of SNAP orchards harvesting robots in the presence of multiple uncalibrated model parameters in the application of dwarf culture orchards harvest. A new hybrid visual servoing…

机器人学 · 计算机科学 2021-06-11 Tao Li , Quan Qiu , Chunjiang Zhao

In this letter, we present a distributed algorithm for flocking in complex environments that operates at constant altitude, without explicit communication, no a priori information about the environment, and by using only on-board sensing…

机器人学 · 计算机科学 2026-03-02 Manuel Boldrer , Vit Kratky , Viktor Walter , Martin Saska

Recent years have seen tremendous advancements in the area of autonomous payload delivery via unmanned aerial vehicles, or drones. However, most of these works involve delivering the payload at a predetermined location using its GPS…

计算机视觉与模式识别 · 计算机科学 2023-10-11 Aditya Vadduri , Anagh Benjwal , Abhishek Pai , Elkan Quadros , Aniruddh Kammar , Prajwal Uday

Site preparation by mounding is a commonly used silvicultural treatment that improves tree growth conditions by mechanically creating planting microsites called mounds. Following site preparation, the next critical step is to count the…

计算机视觉与模式识别 · 计算机科学 2022-09-07 Majid Nikougoftar Nategh , Ahmed Zgaren , Wassim Bouachir , Nizar Bouguila

Agricultural robots must navigate challenging dynamic and semi-structured environments. Recently, environmental modeling using LiDAR-based SLAM has shown promise in providing highly accurate geometry. However, how this chaotic environmental…

机器人学 · 计算机科学 2024-03-29 Yaoqiang Pan , Hao Cao , Kewei Hu , Hanwen Kang , Xing Wang
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