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Inspecting indoor environments such as tunnels, industrial facilities, and construction sites is essential for infrastructure monitoring and maintenance. While manual inspection in these environments is often time-consuming and potentially…

Robotics · Computer Science 2025-04-15 Hanyu Jin , Zhefan Xu , Haoyu Shen , Xinming Han , Kanlong Ye , Kenji Shimada

Unmanned Aerial Vehicles (UAVs) represent a new frontier in a wide range of monitoring and research applications. To fully leverage their potential, a key challenge is planning missions for efficient data acquisition in complex…

Unmanned Aerial Vehicles (UAVs) equipped with high-resolution sensors enable extensive data collection from previously inaccessible areas at a remarkable spatio-temporal scale, promising to revolutionize fields such as precision agriculture…

Robotics · Computer Science 2024-07-19 Harnaik Dhami

In this work, we present a hierarchical framework designed to support robotic inspection under environment uncertainty. By leveraging a known environment model, existing methods plan and safely track inspection routes to visit points of…

Unmanned aerial vehicles (UAVs) are frequently used for aerial mapping and general monitoring tasks. Recent progress in deep learning enabled automated semantic segmentation of imagery to facilitate the interpretation of large-scale complex…

Robotics · Computer Science 2023-09-07 Julius Rückin , Federico Magistri , Cyrill Stachniss , Marija Popović

Unmanned Aerial Systems (UAS) have gained significant traction for their application in infrastructure inspections. However, considering the enormous scale and complex nature of infrastructure, automation is essential for improving the…

Robotics · Computer Science 2023-12-27 Yuxiang Zhao , Benhao Lu , Mohamad Alipour

Unmanned Aerial Vehicles (UAVs) have been implemented for environmental monitoring by using their capabilities of mobile sensing, autonomous navigation, and remote operation. However, in real-world applications, the limitations of on-board…

Robotics · Computer Science 2019-07-16 Teng Li , Chaoqun Wang , Max Q. -H. Meng , Clarence W. de Silva

This paper presents an adaptive coverage control method for a fleet of off-road and Unmanned Ground Vehicles (UGVs) operating in dynamic (time-varying) agricultural environments. Traditional coverage control approaches often assume static…

Robotics · Computer Science 2025-09-09 Sajad Ahmadi , Mohammadreza Davoodi , Javad Mohammadpour Velni

Nowadays, unmanned aerial vehicles or UAVs are being used for a wide range of tasks, including infrastructure inspection, automated monitoring and coverage. This paper investigates the problem of 3D inspection planning with an autonomous…

The task of establishing and maintaining situational awareness in an unknown environment is a critical step to fulfil in a mission related to the field of rescue robotics. Predominantly, the problem of visual inspection of urban structures…

We study the problem of visual surface inspection of infrastructure for defects using an Unmanned Aerial Vehicle (UAV). We do not assume that the geometric model of the infrastructure is known beforehand. Our planner, termed GATSBI, plans a…

Robotics · Computer Science 2024-06-25 Harnaik Dhami , Charith Reddy , Vishnu Dutt Sharma , Troi Williams , Pratap Tokekar

Uncrewed aerial vehicles (UAVs) are increasingly used for exploration-driven monitoring in hazardous environments such as disaster zones, contaminated sites, wildfire areas, and damaged infrastructure, where limited flight endurance must be…

Robotics · Computer Science 2026-05-28 Jimin Choi , Grant Stagg , Cameron K. Peterson , Max Z. Li

Autonomous robotic systems are increasingly deployed for mapping, monitoring, and inspection in complex and unstructured environments. However, most existing path planning approaches remain domain-specific (i.e., either on air, land, or…

Robotics · Computer Science 2026-03-05 Angelos Zacharia , Mihir Dharmadhikari , Mohit Singh , Kostas Alexis

In this paper, a new demonstration-based path-planning framework for the visual inspection of large structures using UAVs is proposed. We introduce UPPLIED: UAV Path PLanning for InspEction through Demonstration, which utilizes a…

This article presents a novel framework for performing visual inspection around 3D infrastructures, by establishing a team of fully autonomous Micro Aerial Vehicles (MAVs) with robust localization, planning and perception capabilities. The…

Target search with unmanned aerial vehicles (UAVs) is relevant problem to many scenarios, e.g., search and rescue (SaR). However, a key challenge is planning paths for maximal search efficiency given flight time constraints. To address…

Robotics · Computer Science 2019-02-28 Ajith Anil Meera , Marija Popovic , Alexander Millane , Roland Siegwart

We present an efficient path planning algorithm for an Unmanned Aerial Vehicle surveying a cluttered urban landscape. A special emphasis is on maximizing area surveyed while adhering to constraints of the UAV and partially known and…

Robotics · Computer Science 2018-09-13 Vaibhav Darbari , Saksham Gupta , Om Prakash Verma

This paper presents an adaptive path planner for object search in agricultural fields using UAVs. The path planner uses a high-altitude coverage flight path and plans additional low-altitude inspections when the detection network is…

Robotics · Computer Science 2025-06-11 Rick van Essen , Eldert van Henten , Lammert Kooistra , Gert Kootstra

In Japan, inspection of irrigation water canals has been mostly conducted manually. However, the huge demand for more regular inspections as infrastructure ages, coupled with the limited time window available for inspection, has rendered…

Robotics · Computer Science 2018-03-08 Di Deng , Tao Pang , Prasanth Palli , Fang Shu , Kenji Shimada

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…

Robotics · Computer Science 2019-06-18 Jesus Tordesillas , Brett T. Lopez , John Carter , John Ware , Jonathan P. How
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