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The motion planning and tracking control techniques of unmanned underwater vehicles (UUV) are fundamentally significant for efficient and robust UUV navigation, which is crucial for underwater rescue, facility maintenance, marine resource…

机器人学 · 计算机科学 2022-07-12 Danjie Zhu , Tao Yan , Simon X. Yang

Autonomous navigation through unknown environments is a challenging task that entails real-time localization, perception, planning, and control. UAVs with this capability have begun to emerge in the literature with advances in lightweight…

机器人学 · 计算机科学 2019-06-18 Jesus Tordesillas , Brett T. Lopez , John Carter , John Ware , Jonathan P. How

Current fifth generation (5G) cellular networks mainly focus on the terrestrial scenario. Due to the difficulty of deploying communications infrastructure on the ocean, the performance of existing maritime communication networks (MCNs) is…

信号处理 · 电气工程与系统科学 2021-03-04 Xiangling Li , Wei Feng , Jue Wang , Yunfei Chen , Ning Ge , Cheng-Xiang Wang

Unmanned aerial vehicles (UAVs) have become very popular for many military and civilian applications including in agriculture, construction, mining, environmental monitoring, etc. A desirable feature for UAVs is the ability to navigate and…

机器人学 · 计算机科学 2021-11-02 Taha Elmokadem

Unmanned Surface Vehicles technology (USVs) is an exciting topic that essentially deploys an algorithm to safely and efficiently performs a mission. Although reinforcement learning is a well-known approach to modeling such a task,…

机器学习 · 计算机科学 2020-03-24 Mohammad Etemad , Nader Zare , Mahtab Sarvmaili , Amilcar Soares , Bruno Brandoli Machado , Stan Matwin

This work describes the orchestration of a fleet of rotary-wing Unmanned Aerial Vehicles (UAVs) for harvesting prioritized traffic from random distributions of heterogeneous users with Multiple Input Multiple Output (MIMO) capabilities. In…

系统与控制 · 电气工程与系统科学 2024-04-02 Bharath Keshavamurthy , Nicolo Michelusi

In this article, we consider a multi-agent path planning problem in a stochastic environment. The environment, which can be an urban road network, is represented by a graph where the travel time for selected road segments (impeded edges) is…

As terrestrial resources become increasingly depleted, the demand for deep-sea resource exploration has intensified. However, the extreme conditions in the deep-sea environment pose significant challenges for underwater operations,…

机器人学 · 计算机科学 2024-10-23 Yinyi Lai , Jiaqi Shang , Zenghui Liu , Zheyu Jiang , Yuyang Li , Longchao Chen

In this paper we address the mine countermeasures (MCM) search problem for an autonomous underwater vehicle (AUV) surveying the seabed using a side-looking sonar. We propose a coverage path planning method that adapts the AUV track spacing…

机器人学 · 计算机科学 2020-06-24 Veronika Yordanova , Bart Gips

This paper investigates the three-dimensional (3D) deployment of uncrewed aerial vehicles (UAVs) as aerial base stations in heterogeneous communication networks under constraints imposed by diverse ground obstacles. Given the diverse data…

信号处理 · 电气工程与系统科学 2026-01-16 Senning Wan , Bin Li , Hongbin Chen , Lei Liu

This letter addresses the problem of trajectory planning in a marsupial robotic system consisting of an unmanned aerial vehicle (UAV) linked to an unmanned ground vehicle (UGV) through a non-taut tether with controllable length. To the best…

机器人学 · 计算机科学 2023-07-27 S. Martínez-Rozas , D. Alejo , F. Caballero , L. Merino

Path Planning methods for autonomous control of Unmanned Aerial Vehicle (UAV) swarms are on the rise because of all the advantages they bring. There are more and more scenarios where autonomous control of multiple UAVs is required. Most of…

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

Autonomous navigation in ice-covered waters poses significant challenges due to the frequent lack of viable collision-free trajectories. When complete obstacle avoidance is infeasible, it becomes imperative for the navigation strategy to…

机器人学 · 计算机科学 2024-09-19 Ninghan Zhong , Alessandro Potenza , Stephen L. Smith

For accomplishing a variety of missions in challenging environments, the capability of navigating with full autonomy while avoiding unexpected obstacles is the most crucial requirement for UAVs in real applications. In this paper, we…

机器人学 · 计算机科学 2020-12-29 Han Chen , Peng Lu

Effective risk monitoring in dynamic environments such as disaster zones requires an adaptive exploration strategy to detect hidden threats. We propose a bi-level unmanned aerial vehicle (UAV) monitoring strategy that efficiently integrates…

最优化与控制 · 数学 2026-01-22 Jimin Choi , Grant Stagg , Cameron K. Peterson , Max Z. Li

Underwater glider robots have become indispensable for ocean sampling, yet fully autonomous long-term operation remains rare in practice. Although stakeholders are calling for tools to manage increasingly large fleets of gliders, existing…

Autonomous surface vessels (ASV) represent a promising technology to automate water-quality monitoring of lakes. In this work, we use satellite images as a coarse map and plan sampling routes for the robot. However, inconsistency between…

机器人学 · 计算机科学 2023-05-01 Yizhou Huang , Hamza Dugmag , Timothy D. Barfoot , Florian Shkurti

Typical marine environments are highly complex with spatio-temporally varying currents and dynamic obstacles, presenting significant challenges to Unmanned Surface Vehicles (USVs) for safe and efficient navigation. Thus, the USVs need to…

机器人学 · 计算机科学 2025-08-14 Reema Raval , Shalabh Gupta

We propose a novel receding horizon planner for an autonomous surface vehicle (ASV) performing path planning in urban waterways. Feasible paths are found by repeatedly generating and searching a graph reflecting the obstacles observed in…

机器人学 · 计算机科学 2020-09-02 Tixiao Shan , Wei Wang , Brendan Englot , Carlo Ratti , Daniela Rus