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Twirre V2: Evolution of an architecture for automated mini-UAVs using interchangeable commodity components

Twirre V2 is the evolution of an architecture for mini-UAV platforms which allows automated operation in both GPS-enabled and GPSdeprived applications. This second version separates mission logic, sensor data processing and high-level control, which results in reusable software components for multiple applications. The concept of Local Positioning System (LPS) is introduced, which, using sensor fusion, would aid or automate the flying process like GPS currently does. For this, new sensors are added to the architecture and a generic sensor interface together with missions for landing and following a line have been implemented. V2 introduces a software modular design and new hardware has been coupled, showing its extensibility and adaptability

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Twirre V2: Evolution of an architecture for automated mini-UAVs using interchangeable commodity components

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Point Cloud Analysis of Railway Infrastructure: A Systematic Literature Review

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Cad Cam in de Orthopedie techniek

Cad Cam in de orthopedie techniek. Een technisch hoofdstuk over het gebruik en de toepassing van Cad Cam technologie in de orthopedie. Dit hoofstuk is onderdeel van het boek " Amputatie en prothesiologie van de onderste extremiteit", onder redactie van prof. dr. J.H.B. Geertzen en dr. J.S. Rietman. Dit boek wordt onder andere gebruitk in de opleiding Revalidatie Geneeskunde en de Hogere Beroepsopleiding Orthopedische Technologie

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Semantic Segmentation of Terrestrial Laser Scans of Railway Catenary Arches: A Use Case Perspective

aving access to accurate and recent digital twins of infrastructure assets benefits the renovation, maintenance, condition monitoring, and construction planning of infrastructural projects. There are many cases where such a digital twin does not yet exist, such as for legacy structures. In order to create such a digital twin, a mobile laser scanner can be used to capture the geometric representation of the structure. With the aid of semantic segmentation, the scene can be decomposed into different object classes. This decomposition can then be used to retrieve cad models from a cad library to create an accurate digital twin. This study explores three deep-learning-based models for semantic segmentation of point clouds in a practical real-world setting: PointNet++, SuperPoint Graph, and Point Transformer. This study focuses on the use case of catenary arches of the Dutch railway system in collaboration with Strukton Rail, a major contractor for rail projects. A challenging, varied, high-resolution, and annotated dataset for evaluating point cloud segmentation models in railway settings is presented. The dataset contains 14 individually labelled classes and is the first of its kind to be made publicly available. A modified PointNet++ model achieved the best mean class Intersection over Union (IoU) of 71% for the semantic segmentation task on this new, diverse, and challenging dataset.

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Analytical Formalism for Data Representation and Object Detection with 2D LiDAR

In mobile robotics, LASER scanners have a wide spectrum of indoor and outdoor applications, both in structured and unstructured environments, due to their accuracy and precision. Most works that use this sensor have their own data representation and their own case-specific modeling strategies, and no common formalism is adopted. To address this issue, this manuscript presents an analytical approach for the identification and localization of objects using 2D LiDARs. Our main contribution lies in formally defining LASER sensor measurements and their representation, the identification of objects, their main properties, and their location in a scene. We validate our proposal with experiments in generic semi-structured environments common in autonomous navigation, and we demonstrate its feasibility in multiple object detection and identification, strictly following its analytical representation. Finally, our proposal further encourages and facilitates the design, modeling, and implementation of other applications that use LASER scanners as a distance sensor.

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Onder de loep

In opdracht van het Groninger Instituut Archeologie van de Rijksuniversiteit Groningen en de Doggerland projectgroep is onderzoek gedaan naar de effectiviteit van de Reflectance Transformation Imaging (RTI) en fotogrammetrie. Deze twee technieken zijn toegepast op kaakfragmenten met gebitselementen uit het Mesolithicum en de Bronstijd om te onderzoeken of het mogelijk is om met deze technieken een verschil in dieet aan te tonen. Daarnaast is de Artec Spider 3D-scanner toegepast op de gebitselementen. Deze scans zijn gemaakt door externen, waarna de resultaten opgenomen zijn in het onderzoek. Uit het onderzoek is gebleken dat het vaststellen van specifieke verschillen van gebitsslijtage tussen jager-verzamelaars en vroege boeren niet mogelijk is op basis van de RTI-techniek en fotogrammetrie. Beide technieken leveren niet de gewenste resultaten. Zo maakt de RTI-techniek enkel een opname van bovenaf, waardoor de zijaanzichten van de gebitselementen niet onderzocht kunnen worden. De fotogrammetrische techniek is niet gedetailleerd genoeg. Zo vloeien verschillende gebitselementen in elkaar over en zijn sommige elementen niet scherp genoeg om met zekerheid vast te stellen of hier überhaupt slijtagesporen op zijn aangetroffen. Desondanks is het wel mogelijk geweest om de slijtagesporen in beeld te brengen met de Artec Spider 3D-scanner. Deze scanner maakt het mogelijk om de specifieke verschijnselen van gebitsslijtage op de gebitselementen uit het Mesolithicum en de Bronstijd in beeld te brengen.

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Semantic Segmentation of Terrestrial Laser Scans of Railway Catenary Arches

Peer-reviewed artikel over semantische segmentatie van point clouds.

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Semantic Segmentation of Terrestrial Laser Scans of Railway Catenary Arches

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A Novel, Non-Contact NDT Scanner Case Study: Thickness Measurement, Debonding and Defects Detection in Metallic and Composite Parts

The NDT methods currently used in aviation MRO are predominantly labour-intensive and time-consuming processes performed by human operators throughout the lifespan of an aircraft. These techniques are time-consuming, require perpetual training and are highly dependent on the operator's skills. Thus, there is a growing need for more efficient, automated, and accurate NDT tools that will be able to provide faster and less labour-intensive assessments. This study presents a novel, non-contact, automated NDT scanning system under development, which aims to reduce the inspection time significantly. The proposed technique uses a non-contact, Lamb wave-based approach. A further essential step during the process is to use an automated positioning system. Thickness mapping and defect detection in metal and composite structures have been performed. A local thickness map in the order of 1 mm has been obtained through a fast-scanning process with comparable resolution to conventional inspection techniques. Overall, it is currently concluded that the proposed NDT scanner is a promising tool that potentially can reduce the inspection time while also having the potential to automate the damage assessment resulting in more efficient MRO inspection processes.

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Products 22

Twirre V2: Evolution of an architecture for automated mini-UAVs using interchangeable commodity components

Point Cloud Analysis of Railway Infrastructure: A Systematic Literature Review

Cad Cam in de Orthopedie techniek

Semantic Segmentation of Terrestrial Laser Scans of Railway Catenary Arches: A Use Case Perspective

Analytical Formalism for Data Representation and Object Detection with 2D LiDAR

Onder de loep

Semantic Segmentation of Terrestrial Laser Scans of Railway Catenary Arches

A Novel, Non-Contact NDT Scanner Case Study: Thickness Measurement, Debonding and Defects Detection in Metallic and Composite Parts

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Products 22

Twirre V2: Evolution of an architecture for automated mini-UAVs using interchangeable commodity components

Point Cloud Analysis of Railway Infrastructure: A Systematic Literature Review

Cad Cam in de Orthopedie techniek

Semantic Segmentation of Terrestrial Laser Scans of Railway Catenary Arches: A Use Case Perspective

Analytical Formalism for Data Representation and Object Detection with 2D LiDAR

Onder de loep

Semantic Segmentation of Terrestrial Laser Scans of Railway Catenary Arches

A Novel, Non-Contact NDT Scanner Case Study: Thickness Measurement, Debonding and Defects Detection in Metallic and Composite Parts