Accuracy evaluation of 3D lidar data from small UAV

Tulldahl, H. Michael; Bissmarck, Fredrik; Larsson, Håkan; Grönwall, Christina; Tolt, Gustav

doi:10.1117/12.2194508

Cited by 26 publications

(32 citation statements)

References 3 publications

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“…UAV orientations rely also on GNSS and IMU devices, and the RMSE of ground points is typically reported to be 0.08-0.09 meters (Jaakkola et al, 2010;Flener et al 2013;Tulldahl et al, 2015). However, the advantage of UAV data collection is that typically there are no obstacles blocking the satellite visibility.…”

Section: Discussionmentioning

confidence: 99%

Quality Analysis and Correction of Mobile Backpack Laser Scanning Data

Rönnholm¹,

Liang²,

Kukko³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission I, WG I/3KEY WORDS: backpack laser scanning, UAV laser scanning, registration, quality, data correction ABSTRACT:Backpack laser scanning systems have emerged recently enabling fast data collection and flexibility to make measurements also in areas that cannot be reached with, for example, vehicle-based laser scanners. Backpack laser scanning systems have been developed both for indoor and outdoor use. We have developed a quality analysis process in which the quality of backpack laser scanning data is evaluated in the forest environment. The reference data was collected with an unmanned aerial vehicle (UAV) laser scanning system. The workflow included noise filtering, division of data into smaller patches, ground point extraction, ground data decimation, and ICP registration. As a result, we managed to observe the misalignments of backpack laser scanning data for 97 patches each including data from circa 10 seconds period of time. This evaluation revealed initial average misalignments of 0.227 m, 0.073 and -0.083 in the easting, northing and elevation directions, respectively. Furthermore, backpack data was corrected according to the ICP registration results. Our correction algorithm utilized the time-based linear transformation of backpack laser scanning point clouds. After the correction of data, the ICP registration was run again. This revealed remaining misalignments between the corrected backpack laser scanning data and the original UAV data. We found average misalignments of 0.084, 0.020 and -0.005 meters in the easting, northing and elevation directions, respectively.

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Section: Discussionmentioning

confidence: 99%

Quality Analysis and Correction of Mobile Backpack Laser Scanning Data

Rönnholm¹,

Liang²,

Kukko³

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Technology advancements allow current LIDAR to be integrated in small UAVs, given the limited weight and cost (for instance, Velodyne Puck LIDAR weights 600 g and costs $8000). Thus, recent works successfully demonstrated the use of small LIDAR sensors on small‐scale MAVs for mapping and autonomous flight …”

Section: Onboard Sensors and Localization And Mappingmentioning

confidence: 99%

Post‐disaster assessment with unmanned aerial vehicles: A survey on practical implementations and research approaches

Recchiuto

Sgorbissa

2017

Journal of Field Robotics

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In this paper, we provide a review of the principal aspects related to search & rescue (SAR) with unmanned aerial vehicles (UAVs), with particular interest in the phase of post-disaster assessment (PDA). Some areas of interest related to this topic have been chosen for the analysis: the aerial platforms used in the field, multirobot software architectures, onboard sensors and simultaneous localization and mapping approaches, terrain coverage algorithms, autonomous navigation techniques, and human-swarm interfaces. All these aspects have been analyzed with respect to the state-of-the-art, and also in relation to the project PRISMA, which focuses on the development and deployment of robots and autonomous systems that can operate in emergency scenarios, with a specific reference to monitoring and real-time intervention

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“…Sallenger et al [14], who extensively tested airborne LiDAR accuracy relative to GPS ground surveys as well as more recent studies wherein where UAV-derived imagery was compared to models derived through terrestrial laser scanning [49,[51][52][53]. To achieve this, we developed three programs of investigation with the objective to evaluate the performance of the Hovermap LiDAR across different environments in effort to better understand system capabilities/limitations and examine the utility of this technology in realistic remote sensing applications.…”

Section: Methodsmentioning

confidence: 99%

“…As a result, decisions may be made on cost/benefit criteria, rather than performance, and lead to from such studies should be considered carefully. Tulldahl et al [49] applied a more refined design incorporating the examination of UAV parameters of flight speed and angular velocity (i.e. pitch, roll, yaw), however, did not discuss the subsequent effects on key point cloud metrics such as the spatial density of sensor returns (points) [50].…”

Section: Knowledge Gapmentioning

confidence: 99%

Examining the utility of Simultaneous Localisation and Mapping (SLAM) LiDAR on a low-altitude unmanned aerial vehicle (UAV) across environments of various composition and dynamic complexity

Sofonia¹

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Rapid technological advancements in aerospace technology and imagery capture have seen a dramatic rise in sensor types available, which has expanded the potential use unmanned aerial vehicles (UAVs) in remote sensing research applications. The proliferation of this technology has resulted in numerous instrument and configuration options available across a broad range of scientific, industrial and management applications, with each configuration having specific strengths and limitations. Information provided by manufacturers, however, is often limited, providing little, or no, information on how these systems may perform across different environments or operating conditions. As a result,

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Accuracy evaluation of 3D lidar data from small UAV

Cited by 26 publications

References 3 publications

Quality Analysis and Correction of Mobile Backpack Laser Scanning Data

Quality Analysis and Correction of Mobile Backpack Laser Scanning Data

Post‐disaster assessment with unmanned aerial vehicles: A survey on practical implementations and research approaches

Examining the utility of Simultaneous Localisation and Mapping (SLAM) LiDAR on a low-altitude unmanned aerial vehicle (UAV) across environments of various composition and dynamic complexity

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