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Dissertationen zum Thema „View Planning Algorithm“

Autor: Grafiati

Veröffentlicht am 25. Mai 2024

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1

Guo, Yixuan. „Hexapod Gait Planning and Obstacle Avoidance Algorithm“. University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1461868607.

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2

Yue, Weiya Ph D. „Improving Dynamic Navigation Algorithms“. University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1368028468.

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3

Suh, Suk-Hwan. „Development of an algorithm for a minimum-time trajectory planning problem under practical considerations /“. The Ohio State University, 1986. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487267546984019.

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4

Joseph, Jose. „UAV Path Planning with Communication Constraints“. University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1563872872304696.

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5

Mathur, Kush. „Mathematical Models and Genetic Algorithm Approaches to Simultaneously Perform Workforce Overtime Capacity Planning and Schedule Cells“. Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1351306927.

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6

Chan, Philip. „Dosimetric verification of the ADAC Pinnacle³ pencil beam algorithm for clinical electrons in presence of cerrobend blocking“. Connect to full text in OhioLINK ETD Center, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=mco1211993729.

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Thesis (M.S.)--University of Toledo, 2008.
"In partial fulfillment of the requirements for the degree of Master of Science in Biomedical Sciences." Title from title page of PDF document. "Date of Defense: December 12, 2007" -- Approval page. Bibliography: p. 71-73.

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7

Rathore, Aishvarya. „Quality Analysis of UAV based 3D Reconstruction and its Applications in Path Planning“. University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627658323958222.

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8

Rajaraman, Srinivas. „Space Search Based Algorithm for Cell Formation with Alternative Process Plans“. Ohio University / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1082146485.

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9

Kingry, Nathaniel. „Heuristic Optimization and Sensing Techniques for Mission Planning of Solar-Powered Unmanned Ground Vehicles“. The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523874767812408.

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10

Lakshminarayanan, Srinivasan. „Nature Inspired Discrete Integer Cuckoo Search Algorithm for Optimal Planned Generator Maintenance Scheduling“. University of Toledo / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1438101954.

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11

Rennu, Samantha R. „Dynamic Mission Planning for Unmanned Aerial Vehicles“. University of Dayton / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton16082274381124.

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12

Elahi, Behin. „Integrated Optimization Models and Strategies for Green Supply Chain Planning“. University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1467266039.

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13

Lafountain, Cody. „Matlab-based Development of Intelligent Systems for Aerospace Applications“. University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1427812775.

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14

Debnath, Jayanta Kumar. „Development of Scheduling, Path Planning and Resource Management Algorithms for Robotic Fully-automated and Multi-story Parking Structure“. University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1470399189.

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15

OLAOYE, ISRAEL A. „WATER QUALITY MODELING OF THE OLD WOMAN CREEK WATERSHED, OHIO, UNDER THE INFLUENCE OF CLIMATE CHANGE TO YEAR 2100“. Kent State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=kent1605955492844115.

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16

Jubert, Manon. „Algorithme de planification de numérisation et d’alignement de nuages de points 3D pour le contrôle in-situ de pièces mécaniques en cours d’usinage“. Electronic Thesis or Diss., Aix-Marseille, 2021. http://www.theses.fr/2021AIXM0233.

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Dans ce travail de thèse, nous traitons le problème de planification de numérisation et nous abordons également la problématique d'alignement de nuages de points 3D. Ces problèmes peuvent être étudiés et globalisés pour répondre aux besoins de nombreux domaines d'études. Dans ce manuscrit, nous répondons à la problématique suivante : comment contrôler automatiquement une pièce mécanique en cours d'usinage ? La première contribution à cette étude est l'élaboration d'un algorithme de planification automatique de numérisation de la pièce en fonction des contrôles à effectuer sur celle-ci. L'approche que nous proposons permet de s'adapter à n'importe quel outil de numérisation optique. La méthode proposée est générale et permet en plus de s'adapter à n'importe quel environnement industriel dans lequel est positionnée la pièce à contrôler. La seconde contribution se focalise sur le cas spécifique des données issues de capteurs optiques, à savoir les nuages de points 3D. À partir du plan de numérisation, nous élaborons une stratégie d'alignement des nuages de points entre eux. Nous abordons la problématique des cas où l'alignement des nuages de points n'est pas possible et tentons de résoudre ce problème. Enfin, on montre plusieurs applications industrielles de ces algorithmes, et nous discutons que la précision des méthodes proposées sur ces cas. On propose plusieurs ouvertures sur la suite de ces travaux, notamment sur les cas spécifiques de pièces non-alignables ou de grande envergure. Des idées d'amélioration et de robustification des algorithmes sont faites pour la suite de la recherche
In this thesis work, we deal with the problem of scan planning and we also address the problem of 3D point clouds alignment. These problems can be studied and globalized to meet the needs of many fields of study. In this manuscript, we answer the following question: how to automatically control a mechanical part during machining? Or more precisely: how to obtain a good representation of the part so as to check its good conformity during the machining process? The first contribution to this study is the development of an automatic algorithm for planning the digitization of the part according to the controls to be carried out on it. The approach allows to adapt to any optical digitizing device. In our study, we show the results of this method on several fringe projection optical sensors and on several industrial parts. The proposed method is general and allows to adapt to any industrial environment in which the part to be controlled is positioned. The second contribution focuses on the specific case of data from optical sensors, i.e. 3D point clouds. From the scanning plan, we develop a strategy for aligning point clouds between them. We address the problem of cases where the alignment of point clouds is not possible and try to solve this problem. Finally, we show several industrial applications of these algorithms, and we study the precision of the methods on these cases. We propose several openings on the continuation of this work, in particular on the specific cases of non-alignable parts or on large parts. Ideas for improvement and robustification of the algorithms are discussed

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17

Wedge, Nathan Alexander. „Sampling-based Motion Planning Algorithms: Analysis and Development“. Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1301502703.

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18

Androulakakis, Pavlos. „Analysis of Evolutionary Algorithms in the Control of Path Planning Problems“. Wright State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright1535549741081137.

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19

Reeves, Megan Clancy. „An Analysis of Path Planning Algorithms Focusing on A* and D*“. University of Dayton / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1557245975528397.

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20

Bradner, Kevin M. „Path Planning for Variable Scrutiny Multi-Robot Coverage“. Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1578915876868832.

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21

SRINIVASAN, SREERAM. „SIMULTANEOUS DIMENSIONAL AND TOLERANCE SYNTHESIS IN PROCESS PLANNING“. University of Cincinnati / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1070493927.

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22

Herrick, Andrea Celeste. „A Comparative Dosimetric Analysis of the Effect of Heterogeneity Corrections Used in Three Treatment Planning Algorithms“. University of Toledo Health Science Campus / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=mco1290427283.

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23

Pfeil, Jonathan W. „Algorithms and Resources for Scalable Natural Language Generation“. Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1465469914.

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24

Freeman, Michael James. „The Integration of Iterative Convergent Photogrammetric Models and UAV View and Path Planning Algorithms into the Aerial Inspection Practices in Areas with Aerial Hazards“. BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8738.

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Small unmanned aerial vehicles (sUAV) can produce valuable data for inspections, topography, mapping, and 3D modeling of structures. Used by multiple industries, sUAV can help inspect and study geographic and structural sites. Typically, the sUAV and camera specifications require optimal conditions with known geography and fly pre-determined flight paths. However, if the environment changes, new undetectable aerial hazards may intersect new flight paths. This makes it difficult to construct autonomous flight path missions that are safe in post-hazard areas where the flight paths are based on previously built models or previously known terrain details. The goal of this research is to make it possible for an unskilled pilot to obtain high quality images at key angles which will facilitate the inspections of dangerous environments affected by natural disasters through the construction of accurate 3D models. An iterative process with converging variables can circumvent the current deficit in flying UAVs autonomously and make it possible for an unskilled pilot to gather high quality data for the construction of photogrammetric models. This can be achieved by gaining preliminary photogrammetric data, then creating new flight paths which consider new developments contained in the generated dense clouds. Initial flight paths are used to develop a coarse representation of the target area by aligning key tie points of the initial set of images. With each iteration, a 3D mesh is used to compute a new optimized view and flight path used for the data collection of a better-known location. These data are collected, the model updated, and a new flight path is computed until the model resolution meets the required heights or ground sample distances (GSD). This research uses basic UAVs and camera sensors to lower costs and reduce the need for specialized sensors or data analysis. The four basic stages followed in the study include: determination of required height reductions for comparison and convergent limitation, construction of real-time reconnaissance models, optimized view and flight paths with vertical and horizontal buffers constructed from previous models, and develop an autonomous process that combines the previous stages iteratively. This study advances the use of autonomous sUAV inspections by developing an iterative process of flying a sUAV to potentially detect and avoid buildings, trees, wires, and other hazards in an iterative manner with minimal pilot experience or human intervention; while optimally collecting the required images to generate geometric models of predetermined quality.

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25

Dou, Chao. „Development of Storage and Retrieval Algorithms for Automated Parking Systems“. University of Toledo / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1333678326.

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26

Chen, Qi. „Studies in autonomous ground vehicle control systems structure and algorithms /“. Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1165959992.

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27

Fallahtafti, Alireza. „Developing Risk-Minimizing Vehicle Routing Problem for Transportation of Valuables: Models and Algorithms“. Ohio University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1627568962315484.

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28

Holtzhausen, Stefan. „Erfassungsplanung nach dem Optimierungsprinzip am Beispiel des Streifenprojektionsverfahrens“. Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-173373.

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Die vorliegende Arbeit befasst sich mit der Erfassung von Oberflächen mittels Streifenprojektionsverfahren. Dabei wird ein Berechnungsmodell erarbeitet, welches den durch eine Aufnahme erfassten Bereich der Objektoberfläche berechnet und bewertet. Mithilfe einer optimalen Positionierung von Einzelaufnahmen ist es möglich, ein Objekt bei festgelegten Randbedingungen zeitsparend zu erfassen.

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29

Lin, Cheng-Yao, und 林正曜. „A Best View Planning Based 3D Full Detail Textured Model Reconstruction Process through DLT and Dense Disparity Mapping Algorithm“. Thesis, 2010. http://ndltd.ncl.edu.tw/handle/75813655841647463533.

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碩士
東海大學
資訊工程學系
98
A fast and precise 3D reconstruction process is proposed. It aims to reconstruct a fine detail photo realistic textured digital model of the real world objects. This process provides a method that apply image feature points matching and alignment of consecutive photos. The taking of photos on real world objects has been planned based on a view planning and view sequencing algorithm. So long as corresponding control points of two photographs align with each other repeatedly, we can offer a coarse model of the original real object as a whole. Once the view sequencing process is complete, we can not only acquire key frames for model reconstruction, but also receive enough information for full detail texture mapping of the digital model. The whole experiment procedure uses DLT calibration, disparity mapping algorithm and Delaunay triangulation for model subdivision. The use of DLT stereo intersection algorithm allows not only stereo model extraction, but also facilitates texture mapping of the object details. Experiment results shows that the 3D reconstruction model with full textured mapping . When combined with the best view planning and sequencing theory, its role is more valuable than original thought in 3D model digitization.

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30

Huang, Yam-Ming, und 黃彥銘. „Online Route Planning: Exploring the Canadian Traveller Problem from an Algorithmic Point of View“. Thesis, 2013. http://ndltd.ncl.edu.tw/handle/gqh895.

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碩士
國立清華大學
工業工程與工程管理學系
101
We investigate online route planning problems, which find real applications in dynamic navigation systems used to avoid traffic congestion. This study focuses on several generalizations of the well-known CANADIAN TRAVELLER PROBLEM (CTP). Given a road network G=(V,E) in which there is a source s and a destination t in V, every edge e in E is associated with two possible distances: original d(e) and jam d^+ (e). A traveller only finds out which one of the two distances of an edge upon reaching an end vertex incident to the edge. The objective is to derive an adaptive strategy for travelling from s to t so that the competitive ratio, which compares the distance traversed with that of the static s, t-shortest path in hindsight, is minimized. This problem was initiated by Papadimitriou and Yannakakis. They proved that it is PSPACE-complete to obtain an algorithm with a bounded competitive ratio. In this study, we propose tight lower bounds of the problem when the number of traffic jams is a given constant k, and introduce a deterministic algorithm with a min{r,2k+1}-ratio, which meets the proposed lower bound, where r is the worst-case performance ratio. We also study an extension to the metric Travelling Salesman Problem (TSP) and propose a touring strategy within an O(√k)-competitive ratio. Finally, we discuss randomized strategies, in the hope of surpassing the barrier of obtaining better approximation algorithms.

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