Thematische Bibliographien / Velodyne LiDAR

Inhaltsverzeichnis

  1. Zeitschriftenartikel
  2. Dissertationen
  3. Konferenzberichte

Auswahl der wissenschaftlichen Literatur zum Thema „Velodyne LiDAR“

Autor: Grafiati
Veröffentlicht am 28. Juni 2021
Zuletzt aktualisiert am 4. Februar 2022

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Zeitschriftenartikel zum Thema "Velodyne LiDAR"

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Alsadik, Bashar. "Performance Assessment of Mobile Laser Scanning Systems Using Velodyne Hdl-32e." Surveying and Geospatial Engineering Journal 1, no. 1 (2021): 28–33. http://dx.doi.org/10.38094/sgej116.

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Mapping systems using multi-beam LiDARs are widely used nowadays for different geospatial applications graduating from indoor projects to outdoor city-wide projects. These mobile mapping systems can be either ground-based or aerial-based systems and are mostly equipped with inertial navigation systems INS. The Velodyne HDL-32 LiDAR is a well-known 360° spinning multi-beam laser scanner that is widely used in outdoor and indoor mobile mapping systems. The performance of such LiDARs is an ongoing research topic which is quite important for the quality assurance and quality control topic. The per
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Jozkow, G., C. Toth, and D. Grejner-Brzezinska. "UAS TOPOGRAPHIC MAPPING WITH VELODYNE LiDAR SENSOR." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 2, 2016): 201–8. http://dx.doi.org/10.5194/isprsannals-iii-1-201-2016.

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Unmanned Aerial System (UAS) technology is nowadays willingly used in small area topographic mapping due to low costs and good quality of derived products. Since cameras typically used with UAS have some limitations, e.g. cannot penetrate the vegetation, LiDAR sensors are increasingly getting attention in UAS mapping. Sensor developments reached the point when their costs and size suit the UAS platform, though, LiDAR UAS is still an emerging technology. One issue related to using LiDAR sensors on UAS is the limited performance of the navigation sensors used on UAS platforms. Therefore, various
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Jozkow, G., C. Toth, and D. Grejner-Brzezinska. "UAS TOPOGRAPHIC MAPPING WITH VELODYNE LiDAR SENSOR." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-1 (June 2, 2016): 201–8. http://dx.doi.org/10.5194/isprs-annals-iii-1-201-2016.

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Unmanned Aerial System (UAS) technology is nowadays willingly used in small area topographic mapping due to low costs and good quality of derived products. Since cameras typically used with UAS have some limitations, e.g. cannot penetrate the vegetation, LiDAR sensors are increasingly getting attention in UAS mapping. Sensor developments reached the point when their costs and size suit the UAS platform, though, LiDAR UAS is still an emerging technology. One issue related to using LiDAR sensors on UAS is the limited performance of the navigation sensors used on UAS platforms. Therefore, various
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Tazir, M. L., and N. Seube. "COMPARISON OF UAV LIDAR ODOMETRY OF ROTATING AND FIXED VELODYNE PLATFORMS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 527–34. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-527-2020.

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Abstract. Three-dimensional LiDAR rangefinders are increasingly integrated into unmanned aerial vehicles (UAV), due to their direct access to 3D information, their high accuracy and high refresh rate, and their tendency to be lightweight and cheaper. However, all commercial LiDARs can only offer a limited vertical resolution. To cope with this problem, a solution can be to rotate the LiDAR on an axis passing through its center, adding an additional degree of freedom and allowing more overlap, which significantly enlarges the sensor scope and allows having a complete spherical field of view (FO
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Okunsky, M. V., and N. V. Nesterova. "Velodyne LIDAR method for sensor data decoding." IOP Conference Series: Materials Science and Engineering 516 (April 26, 2019): 012018. http://dx.doi.org/10.1088/1757-899x/516/1/012018.

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Atanacio-Jiménez, Gerardo, José-Joel González-Barbosa, Juan B. Hurtado-Ramos, et al. "LIDAR Velodyne HDL-64E Calibration Using Pattern Planes." International Journal of Advanced Robotic Systems 8, no. 5 (2011): 59. http://dx.doi.org/10.5772/50900.

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This work describes a method for calibration of the Velodyne HDL-64E scanning LIDAR system. The principal contribution was expressed by a pattern calibration signature, the mathematical model and the numerical algorithm for computing the calibration parameters of the LIDAR. In this calibration pattern the main objective is to minimize systematic errors due to geometric calibration factor. It describes an algorithm for solution of the intrinsic and extrinsic parameters. Finally, its uncertainty was calculated from the standard deviation of calibration result errors.
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Zhang, Liang, Qingquan Li, Ming Li, Qingzhou Mao, and Andreas Nüchter. "Multiple Vehicle-like Target Tracking Based on the Velodyne LiDAR*." IFAC Proceedings Volumes 46, no. 10 (2013): 126–31. http://dx.doi.org/10.3182/20130626-3-au-2035.00058.

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Erke, Shang, Dai Bin, Nie Yiming, Xiao Liang, and Zhu Qi. "A fast calibration approach for onboard LiDAR-camera systems." International Journal of Advanced Robotic Systems 17, no. 2 (2020): 172988142090960. http://dx.doi.org/10.1177/1729881420909606.

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Outdoor surveillance and security robots have a wide range of industrial, military, and civilian applications. In order to achieve autonomous navigation, the LiDAR-camera system is widely applied by outdoor surveillance and security robots. The calibration of the LiDAR-camera system is essential and important for robots to correctly acquire the scene information. This article proposes a fast calibration approach that is different from traditional calibration algorithms. The proposed approach combines two independent calibration processes, which are the calibration of LiDAR and the camera to ro
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Lassiter, H. Andrew, Travis Whitley, Benjamin Wilkinson, and Amr Abd-Elrahman. "Scan Pattern Characterization of Velodyne VLP-16 Lidar Sensor for UAS Laser Scanning." Sensors 20, no. 24 (2020): 7351. http://dx.doi.org/10.3390/s20247351.

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Many lightweight lidar sensors employed for UAS lidar mapping feature a fan-style laser emitter-detector configuration which results in a non-uniform pattern of laser pulse returns. As the role of UAS lidar mapping grows in both research and industry, it is imperative to understand the behavior of the fan-style lidar sensor to ensure proper mission planning. This study introduces sensor modeling software for scanning simulation and analytical equations developed in-house to characterize the non-uniform return density (i.e., scan pattern) of the fan-style sensor, with special focus given to a p
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Bula, Jason, Marc-Henri Derron, and Gregoire Mariethoz. "Dense point cloud acquisition with a low-cost Velodyne VLP-16." Geoscientific Instrumentation, Methods and Data Systems 9, no. 2 (2020): 385–96. http://dx.doi.org/10.5194/gi-9-385-2020.

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Abstract. This study develops a low-cost terrestrial lidar system (TLS) for dense point cloud acquisition. Our system consists of a VLP-16 lidar scanner produced by Velodyne, which we have placed on a motorized rotating platform. This allows us to continuously change the direction and densify the scan. Axis correction is performed in post-processing to obtain accurate scans. The system has been compared indoors with a high-cost system, showing an average absolute difference of ±2.5 cm. Stability tests demonstrated an average distance of ±2 cm between repeated scans with our system. The system
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Dissertationen zum Thema "Velodyne LiDAR"

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Zhao, Guanyi. "Fusion of Ladybug3 omnidirectional camera and Velodyne Lidar." Thesis, KTH, Geodesi och satellitpositionering, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-172431.

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The advent of autonomous vehicles expedites the revolution of car industry. Volvo Car Corporation has an ambition of developing the next generation of autonomous vehicle. In the Volvo Car Corporation, Active Safety CAE group, enthusiastic engineers have initiated a series of relevant research to enhance the safety function for autonomous vehicle and this thesis work is also implemented at Active Safety CAE with their support.    Perception of vehicle plays a pivotal role in autonomous driving, therefore an idea of improving vision by fusing two different types of data from Velodyne HDL-64E S3
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Zhang, Erik. "Integration of IMU and Velodyne LiDAR sensor in an ICP-SLAM framework." Thesis, KTH, Optimeringslära och systemteori, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-193653.

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Simultaneous localization and mapping (SLAM) of an unknown environment is a critical step for many autonomous processes. For this work, we propose a solution which does not rely on storing descriptors of the environment and performing descriptors filtering. Compared to most SLAM based methods this work with general sparse point clouds with the underlying generalized ICP (GICP) algorithm for point cloud registration. This thesis presents a modified GICP method and an investigation of how and if an IMU can assist the SLAM process by different methods of integrating the IMU measurements. All the
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Marko, Peter. "Detekce objektů v laserových skenech pomocí konvolučních neuronových sítí." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445509.

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This thesis is aimed at detection of lines of horizontal road markings from a point cloud, which was obtained using mobile laser mapping. The system works interactively in cooperation with user, which marks the beginning of the traffic line. The program gradually detects the remaining parts of the traffic line and creates its vector representation. Initially, a point cloud is projected into a horizontal plane, crating a 2D image that is segmented by a U-Net convolutional neural network. Segmentation marks one traffic line. Segmentation is converted to a polyline, which can be used in a geo-inf
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Kannan, Krishnaswamy. "Development of a reference software platform for the Velodyne VLP-16 LiDARS." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-206080.

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Recent advancements in sensor technologies have paved the way towards the realization of autonomous vehicles. The choice of sensors used in such vehicles plays a pivotal role in their successful operation under different conditions. The sensors used in the current generation semi-autonomous vehicles provide a reliable performance for normal use cases. However, their reliability significantly reduces for extreme use cases due to their sensing limitations such as, poor sensitivity to certain materials, limited range, restricted field of view (blind spots), and so on. Hence, a deeper understandin
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Lin, Ying-chen, and 林映辰. "Large scale 3D scene registration using data from Velodyne LIDAR." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/90027455243843548464.

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碩士<br>國立高雄大學<br>資訊工程學系碩士班<br>99<br>With the rapid development of 3D computing technology, the acquisition of range data has become a necessary activity for numerous applications. Large scene reconstruction, which aims to gather depth information of the environment by the use of some range sensors, is a challenging problem. It is considered challenging because the scale of scanned data is relatively large than any regular sized object. Laser rangefinders are perhaps the most frequently used sensors in the applications of scene reconstruction. In our work a 3D reconstruction system that equips w
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Konferenzberichte zum Thema "Velodyne LiDAR"

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Velas, Martin, Michal Spanel, Michal Hradis, and Adam Herout. "CNN for IMU assisted odometry estimation using velodyne LiDAR." In 2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2018. http://dx.doi.org/10.1109/icarsc.2018.8374163.

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Bergelt, Rene, Owes Khan, and Wolfram Hardt. "Improving the intrinsic calibration of a Velodyne LiDAR sensor." In 2017 IEEE SENSORS. IEEE, 2017. http://dx.doi.org/10.1109/icsens.2017.8234357.

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Velas, Martin, Michal Spanel, Michal Hradis, and Adam Herout. "CNN for very fast ground segmentation in velodyne LiDAR data." In 2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE, 2018. http://dx.doi.org/10.1109/icarsc.2018.8374167.

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Halterman, Ryan, and Michael Bruch. "Velodyne HDL-64E lidar for unmanned surface vehicle obstacle detection." In SPIE Defense, Security, and Sensing, edited by Grant R. Gerhart, Douglas W. Gage, and Charles M. Shoemaker. SPIE, 2010. http://dx.doi.org/10.1117/12.850611.

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Solis, E. D. Bravo, A. Miranda Neto, and B. Nina Huallpa. "Pearson's Correlation Coefficient for Discarding Redundant Information: Velodyne Lidar Data Analysis." In 2015 12th Latin American Robotics Symposium (LARS) and 2015 3rd Brazilian Symposium on Robotics (LARS-SBR). IEEE, 2015. http://dx.doi.org/10.1109/lars-sbr.2015.34.

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Chu, Phuong Minh, Seoungjae Cho, Sungdae Sim, Kiho Kwak, Yong Woon Park, and Kyungeun Cho. "Removing past data of dynamic objects using static Velodyne LiDAR sensor." In 2016 16th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2016. http://dx.doi.org/10.1109/iccas.2016.7832519.

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Yu, Yong, Zhenhai Gao, Bing Zhu, and Jian Zhao. "Recognition and Classification of Vehicle Target Using the Vehicle-Mounted Velodyne LIDAR." In SAE 2014 World Congress & Exhibition. SAE International, 2014. http://dx.doi.org/10.4271/2014-01-0322.

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Goll, Stanislav A., Sergey S. Luksha, Vladimir S. Leushkin, and Alexandr G. Borisov. "Construction of the local patency map on the data from Velodyne LiDAR." In 2016 5th Mediterranean Conference on Embedded Computing (MECO). IEEE, 2016. http://dx.doi.org/10.1109/meco.2016.7525736.

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Oh, Seontaek, Ji-Hwan Yu, Azim Eskandarian, and Young-Keun Kim. "Design of Yaw and Tilt Alignment Inspection System for a Low-Resolution 3D LiDAR Using Planar Target." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23601.

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Abstract It is crucial to attach a LiDAR (Light Detection and Ranging), a 3D sensor for a mobile platform such as robot and vehicle within the acceptable misalignment to detect the relative positions of surrounding obstacles accurately. This paper proposes a novel inspection method to estimate the yaw and tilt alignment of a LiDAR after the sensor attachment. The proposed method uses a planar target board to estimate the yaw and tilt angles of a low-resolution LiDAR with milli-degree precision. Experiments were conducted to evaluate the accuracy and precision of the proposed method with the de
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Akhtar, Rayyan, Huabiao Qin, and Guancheng Chen. "Velodyne LiDAR and monocular camera data fusion for depth map and 3D reconstruction." In Eleventh International Conference on Digital Image Processing, edited by Xudong Jiang and Jenq-Neng Hwang. SPIE, 2019. http://dx.doi.org/10.1117/12.2539863.

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