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相关论文: Towards Multi-robot Exploration: A Decentralized S…

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In this study, we present a novel hybrid algorithm, combining Levy Flight (LF) and Particle Swarm Optimization (PSO) (LF-PSO), tailored for efficient multi-robot exploration in unknown environments with limited communication and no global…

A system of cooperative unmanned aerial vehicles (UAVs) is a group of agents interacting with each other and the surrounding environment to achieve a specific task. In contrast with a single UAV, UAV swarms are expected to benefit…

系统与控制 · 电气工程与系统科学 2019-08-09 Arman Sargolzaei , Alireza Abbaspour , Carl D. Crane

The area coverage problem is the task of efficiently servicing a given two-dimensional surface using sensors mounted on robots such as unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). We present a novel formulation for…

机器人学 · 计算机科学 2022-08-23 Saurav Agarwal , Srinivas Akella

Unmanned aerial vehicle (UAV) swarm control has applications including target tracking, surveillance, terrain mapping, and precision agriculture. Decentralized control methods are particularly useful when the swarm is large, as centralized…

系统与控制 · 电气工程与系统科学 2021-07-13 Md Ali Azam

In this paper, we propose a distributed solution to the navigation of a population of unmanned aerial vehicles (UAVs) to best localize a static source. The network is considered heterogeneous with UAVs equipped with received signal strength…

信号处理 · 电气工程与系统科学 2020-07-23 Anna Guerra , Davide Dardari , Petar M. Djuric

The importance of ground Mobile Robots (MRs) and Unmanned Aerial Vehicles (UAVs) within the research community, industry, and society is growing fast. Many of these agents are nowadays equipped with communication systems that are, in some…

机器人学 · 计算机科学 2024-04-04 Daniel Bonilla Licea , Mounir Ghogho , Martin Saska

This paper addresses the problem of target detection and localisation in a limited area using multiple coordinated agents. The swarm of Unmanned Aerial Vehicles (UAVs) determines the position of the dispersion of stack effluents to a gas…

机器人学 · 计算机科学 2019-07-18 Daniele Facinelli , Matteo Larcher , Davide Brunelli , Daniele Fontanelli

Robots will bring search and rescue (SaR) in disaster response to another level, in case they can autonomously take over dangerous SaR tasks from humans. A main challenge for autonomous SaR robots is to safely navigate in cluttered…

机器人学 · 计算机科学 2025-05-07 Karlo Rado , Mirko Baglioni , Anahita Jamshidnejad

Efficient data collection methods play a major role in helping us better understand the Earth and its ecosystems. In many applications, the usage of unmanned aerial vehicles (UAVs) for monitoring and remote sensing is rapidly gaining…

计算机视觉与模式识别 · 计算机科学 2022-03-04 Felix Stache , Jonas Westheider , Federico Magistri , Cyrill Stachniss , Marija Popović

This paper presents a novel strategy for autonomous teamed exploration of subterranean environments using legged and aerial robots. Tailored to the fact that subterranean settings, such as cave networks and underground mines, often involve…

The challenge of efficient target searching in vast natural environments has driven the need for advanced multi-UAV active search strategies. This paper introduces a novel method in which global and local information is adeptly merged to…

机器人学 · 计算机科学 2024-06-25 Chuanxiang Gao , Xinyi Wang , Xi Chen , Ben M. Chen

Unmanned Aerial Vehicles (UAVs) have revolutionized inspection tasks by offering a safer, more efficient, and flexible alternative to traditional methods. However, battery limitations often constrain their effectiveness, necessitating the…

There is increasing demand for control of multi-robot and as well distributing large amounts of content to cluster of Unmanned Aerial Vehicles (UAV) on the operation. In recent years several large-scale accidents have happened. To…

信号处理 · 电气工程与系统科学 2020-08-18 Rahim Rahmani , Ramin Firouzi , Theo Kanter

Indoor exploration is an important task in disaster relief, emergency response scenarios, and Search And Rescue (SAR) missions. Unmanned Aerial Vehicle (UAV) systems can aid first responders by maneuvering autonomously in areas inside…

机器人学 · 计算机科学 2022-05-30 Adil Farooq , Christos Laoudias , Panayiotis S. Kolios , Theocharis Theocharides

Optimal transport (OT) is a framework that can guide the design of efficient resource allocation strategies in a network of multiple sources and targets. This paper applies discrete OT to a swarm of UAVs in a novel way to achieve…

多智能体系统 · 计算机科学 2022-12-01 Jason Hughes , Dominic Larkin , Charles O'Donnell , Christopher Korpela

The complete collection of sparse resources in large, unknown environments remains a challenging problem for autonomous robot swarms. Previous studies have shown that a substantial portion of total mission time is consumed during the final…

机器人学 · 计算机科学 2026-05-22 Qi Arturo Gonzalez , Yifeng Gao , Li Zhang , Qi Lu

This study proposes an efficient data collection strategy exploiting a team of Unmanned Aerial Vehicles (UAVs) to monitor and collect the data of a large distributed sensor network usually used for environmental monitoring, meteorology,…

机器人学 · 计算机科学 2021-01-12 S. MahmoudZadeh , A. Yazdani , A. Elmi , A. Abbasi , P. Ghanooni

This paper systematically studies the cooperative area coverage and target tracking problem of multiple-unmanned aerial vehicles (multi-UAVs). The problem is solved by decomposing into three sub-problems: information fusion, task…

多智能体系统 · 计算机科学 2023-03-17 Mengge Zhang , Jie Li , Xiangke Wang

This paper studies optimal unmanned aerial vehicle (UAV) placement to ensure line-of-sight (LOS) communication and sensing for a cluster of ground users possibly in deep shadow, while the UAV maintains backhaul connectivity with a base…

系统与控制 · 电气工程与系统科学 2024-09-04 Yuanshuai Zheng , Junting Chen

Unmanned aerial vehicles (UAVs) have attracted plenty of attention due to their high flexibility and enhanced communication ability. However, the limited coverage and energy of UAVs make it difficult to provide timely wireless service for…

系统与控制 · 电气工程与系统科学 2024-12-18 Rui Wang , Kaitao Meng , Deshi Li