An experimental investigation into ALS uncertainty and its impact on environmental applications

This study takes an experimental approach to investigating the reliability and repeatability of an airborne laser scanning (ALS) survey. The ability to characterise an area precisely in 3-D using ALS is essential for multi-temporal analysis where change detection is an important application. The reliability and consistency between two ALS datasets is discussed in the context of uncertainty within a single epoch and in the context of well known point- and grid-based descriptors and metrics. The implications of repeatability, verifiability and reliability are discussed in the context of environmental applications, specifically concerning forestry where high resolution ALS surveys are commonly used for forest mensuration over large areas. The study used a regular 10-by-10 layout of standard school tables and decreased the separation from 2.5 metres apart to 0.5 metres in order to evaluate the effects of object separation on their detection. Each configuration was scanned twice using the same ALS scanning parameters and the difference between the datasets is investigated and discussed. The results quantify uncertainty in the ability of ALS to characterise objects, estimate vertical heights and interpret features / objects with certainty. The results show that repeat scanning of the same features under the same conditions result in a laser point cloud with different properties. Objects that are expected to be present in 40 points per metre2 laser point cloud are absent, and the investigation reveals that irregular point spacing and lack of consideration of the ALS footprint size and the interaction with the object of interest are significant factors in the detection and characterisation of features. The results strongly suggest that characterisation of error is important and relevant to environmental applications that use multi-epoch ALS or data with high resolution / point density for object detection and characterisatio

Implementation of a collaborative robot application for closures' quality control

Among the processes that SACMI IMOLA s.c.r.l has internally, quality control certainly plays a fundamental role. In particular, Between all the automatic machines that the company produces, the CCM48, a continuous compression moulding machine able, though 48 pistons, to create over 2000 plastic closures / min with max closure diameter 38 mm, is under the lens. The intent to make the machine competitive on the market leads to the necessity to create an excellent product. This makes quality control of the latter, an aspect of fundamental importance. In this regard, today the closure's control quality procedure is made by two operators that manually, cooperate together. The task is characterized by: LOW frequency, the quality control analysis is realized only once a day on a batch; HIGH repetability, the complete procedure need to be iterate for each cap. Moreover, the operations that are performed by the operators, might be automated through: selection of proper vision sensors for images acquisition, computer vision's algorithms for defects detection and robotic product handling. This is precisely the work that has been carried out in this industrial thesis. The goal is to increase the level of automation in the inspection of the product to highlight possible defects in the process and therefore in the machine. For this purpose, as will be highlighted later, it has been evaluated the possibility to install a collaborative robot to perform this task. The main reason is due to the necessity to do not enormously modify the environment, considering to let the operator works with the robot in a shared workspace. All the source code used to simulate the environment is available on the personal gitHub account \url{https://github.com/EdoardoG94/ThesisFolder}

Reliability of Direct Georeferencing Phase 1: An Overview of the Current Approaches and Possibilities., Checking and Improving of Digital Terrain Models / Reliability of Direct Georeferencing.

After some initial hesitations, the direct georeferencing (DG) of airborne sensors by GPS/INS is now a widely accepted approach in the airborne mapping industry. Implementing DG not only speeds up the mapping process and thus increases the productivity, but also opens the door to new monitoring applications. Although the system manufactures tend to claim that DG is a well established technique and no longer a research topic, the technology users often encounter pitfalls due to undetected sensor behavior, varying data quality and consistency. One could almost clair that the reliability of DG is the Achilles'heel of this otherwise revolutionary approach in civil airborne mapping. EuroSDR has recognized this problem and would like to address it in several phases. First phase of this effort are some preliminary investigations, charting the current situation and making suggestions for further research. The investigations are divided into the following technology fields: GNSS, inertial sensors and estimation methods, integrity and communication, calibration and integrated sensor orientation. Each field describes the current situation with respect to DG and discusses additional existing possibilities. These do not claim to be complete or exhaustive; however, they claim to address the essential features, methods and processes, the combination of which could increase the reliability of DG substantially without setting large side penalties

Моделі, алгоритми та програмне забезпечення для планування шляху для навігації мобільних роботів з уникненням перешкод на основі дерева октантів

Об'єкт дослідження: процес оптимізації та покращення точності руху та уникнення перешкод для навігації мобільних роботів. Предмет дослідження: моделі та методи виявлення перешкод та навігації з метою уникнення виявлених перешкод. Мета магістерської роботи: підвищення ефективності системи розпізнавання перешкод мобільними роботами для навігації у середовищі, використовуючи датчики для забезпечення дороги без зіткнень з об’єктами, які не знаходяться на одному рівні з лазерами. Методи дослідження. Для вирішення поставлених задач використані методи: пошуку шляхів, порогового значення, обробки хмари точок, генерації дерева октантів. Наукова новизна полягає у тому, що удосконалено методи системи планування шляху для навігації мобільних роботів на основі дерева октантів для якісного та точного шляху від початкової точки до заданої у просторі

Application of advanced technology to space automation

Automated operations in space provide the key to optimized mission design and data acquisition at minimum cost for the future. The results of this study strongly accentuate this statement and should provide further incentive for immediate development of specific automtion technology as defined herein. Essential automation technology requirements were identified for future programs. The study was undertaken to address the future role of automation in the space program, the potential benefits to be derived, and the technology efforts that should be directed toward obtaining these benefits

Human-Robot Collaboration in Automotive Industry

Human–Robot Collaboration is a new trend in the field of industrial and service. Application of human-robot-collaboration techniques in automotive industries has many advantages on productivity, production quality and workers’ ergonomic; however, workers’ safety aspects play the vital role during this collaboration. Previously, the machine is allowed to be at automatic work only if operators are out of its workspace but today collaborative robots provide the opportunity to establish the human robot cooperation. In this thesis, efforts have been made to present innovative solutions for using human-robot collaboration to develop a manufacturing cell. These solutions are not only used to facilitate the operator working with collaborative robots but also consider the worker safety and ergonomic. After proposing different solutions for improving the safety of operations during the collaboration with industrial robots, the efficiency of the solutions is tested in both laboratory and virtual environments. In this research, firstly, Analytic Hierarchy Process (AHP) has been used as a potential decision maker to prove the efficiency of human-robot collaboration system over the manual one. In the second step, detailed task decomposition has been done using Hierarchical Task Analysis (HTA) to allocate operational tasks to human and robot reducing the chance of duty interference. In the International Organization of Standardization's technical specification 15066 on collaborative robot safety four methodologies have been proposed to reduce the risk of injury in the work area. The four methods implied in ISO/TS 15066 are safety-rated monitored stop (SMS), hand-guided (HG), speed and separation monitoring (SSM) and power force limiting (PFL). SMS method reduces the risk of operator’s injury by stopping the robot motion whenever the operator is in the collaborative workspace. HG method reduces the chance of operator’s injury by providing the possibility of having control over the robot motion at all times in the workstation using emergency system or enabling device. The SSM method determines the minimum protective distance between a robot and an operator in the collaborative workspace, below which the robot will stop any kind of motion and PFL method reduces the momentum of a robot in a way that contact between an operator and the robot will not cause any injury. After determining the requirements and specifications of hybrid assembly cell, few of the above-mentioned methods for evaluating the safety of human-robot-collaboration procedure have been tasted in the laboratory environment. Due to the lack of safety camera (sensors) in the laboratory workstation, the ISO methods such as SSM, that needs sensors in the workstation, have been modeled in virtual environment to evaluate different scenario of human-robot-interaction and feasibility of the assembly process. Implementing different scenarios of ISO methods in hybrid assembly workstation not only improves the operator safety who is in interaction with the collaborative robot but also improves the worker ergonomic during the performing of repetitive heavy tasks

Update urban basemap by using the LiDAR mobile mapping system : the case of Abu Dhabi municipal system

Basemaps are the main resource used in urban planning and in building and infrastructure asset management. These maps are used by citizens and by private and public stakeholders. Therefore, accurate, up-to-date geoinformation of reference are needed to provide a good service. In general, basemaps have been updated by aerial photogrammetry or field surveying, but these methods are not always possible and alternatives need to be sought. Current limitations and challenges that face traditional field surveys include areas with extreme weather, deserts or artic environments, and flight restrictions due to proximity with other countries if there is not an agreement. In such cases, alternatives for large-scale are required. This thesis proposes the use of a mobile mapping system (MMS) to update urban basemaps. Most urban features can be extracted from point cloud using commercial software or open libraries. However, there are some exceptions: manhole covers, or hidden elements even with captures from defferent perspective, the most common building corners. Therefore, the main objective of this study was to establish a methodology for extracting manholes automatically and for completing hidden corners of buildings, so that urban basemaps can be updated. The algorithm developed to extract manholes is based on time, intensity and shape detection parameters, whereas additional information from satellite images is used to complete buildings. Each municipality knows the materials and dimensions of its manholes. Taking advantage of this knowledge, the point cloud is filtered to classify points according to the set of intensity values associated with the manhole material. From the classified points, the minimum bounding rectangles (MBR) are obtained and finally the shape is adjusted and drawn. We use satellite imagery to automatically digitize the layout of building footprints with automated software tools. Then, the visible corners of buildings from the LiDAR point cloud are imported and a fitting process is performed by comparing them with the corners of the building from the satellite image. Two methods are evaluated to establish which is the most suitable for adjustment in these conditions. In the first method, the differences in X and Y directions are measured in the corners, where LiDAR and satellite data are available, and is often computed as the average of the offsets. In the second method, a Helmert 2D transformation is applied. MMS involves Global Navigation Satellite Systems (GNSS) and Inertial Measurement Units (IMU) to georeference point clouds. Their accuracy depends on the acquisition environment. In this study, the influence of the urban pattern is analysed in three zones with varied urban characteristics: different height buildings, open areas, and areas with a low and high level of urbanization. To evaluate the efficiency of the proposed algorithms, three areas were chosen with varying urban patterns in Abu Dhabi. In these areas, 3D urban elements (light poles, street signs, etc) were automatically extracted using commercial software. The proposed algorithms were applied to the manholes and buildings. The completeness and correctness ratio, and geometric accuracy were calculated for all urban elements in the three areas. The best success rates (>70%) were for light poles, street signs and road curbs, regardless of the height of the buildings. The worst rate was obtained for the same features in peri-urban areas, due to high vegetation. In contrast, the best results for trees were found in theses areas. Our methodology demonstrates the great potential and efficiency of mobile LiDAR technology in updating basemaps; a process that is required to achieve standard accuracy in large scale maps. The cost of the entire process and the time required for the proposed methodology was calculated and compared with the traditional method. It was found that mobile LiDAR could be a standard cost-efficient procedure for updating maps.La cartografía de referencia es la principal herramienta en planificación urbanística, y gestión de infraestructuras y edificios, al servicio de ciudadanos, empresas y administración. Por esta razón, debe estar actualizada y ser lo más precisa posible. Tradicionalmente, la cartografía se actualiza mediante fotogrametría aérea o levantamientos terrestres. No obstante, deben buscarse alternativas válidas para escalas grandes, porque no siempre es posible emplear estas técnicas debido a las limitaciones y retos actuales a los que se enfrenta la medición tradicional en algunas zonas del planeta, con meteorología extrema o restricciones de vuelo por la proximidad a la frontera con otros países. Esta tesis propone el uso del sistema Mobile Mapping System (MMS) para actualizar la cartografía urbana de referencia. La mayoría de los elementos pueden extraerse empleando software comercial o librerías abiertas, excepto los registros de servicios. Los elementos ocultos son otro de los inconvenientes encontrados en el proceso de creación o actualización de la cartografía, incluso si se dispone de capturas desde diferentes puntos de vista. El caso más común es el de las esquinas de edificios. Por ello, el principal objetivo de este estudio es establecer una metodología de extracción automática de los registros y completar las esquinas ocultas de los edificios para actualizar cartografía urbana. El algoritmo desarrollado para la detección y extracción de registros se basa en parámetros como el tiempo, la intensidad de la señal laser y la forma de los registros, mientras que para completar los edificios se emplea información adicional de imágenes satélite. Aprovechando el conocimiento del material y dimensión de los registros, en disposición de los gestores municipales, el algoritmo propuesto filtra y clasifica los puntos de acuerdo a los valores de intensidad. De aquellos clasificados como registros se calcula el mínimo rectángulo que los contiene (Minimum Bounding Rectangle) y finalmente se ajusta la forma y se dibuja. Las imágenes de satélite son empleadas para obtener automáticamente la huella de los edificios. Posteriormente, se importan las esquinas visibles de los edificios obtenidas desde la nube de puntos y se realiza el ajuste comparándolas con las obtenidas desde satélite. Para llevar a cabo este ajuste se han evaluado dos métodos, el primero de ellos considera las diferencias entre las coordenadas XY, desplazándose el promedio. En el segundo, se aplica una transformación Helmert2D. MMS emplea sistemas de navegación global por satélite (Global Navigation Satellite Systems, GNSS) e inerciales (Inertial Measurement Unit, IMU) para georreferenciar la nube de puntos. La precisión de estos sistemas de posicionamiento depende del entorno de adquisición. Por ello, en este estudio se han seleccionado tres áreas con distintas características urbanas (altura de edificios, nivel de urbanización y áreas abiertas) de Abu Dhabi con el fin de analizar su influencia, tanto en la captura, como en la extracción de los elementos. En el caso de farolas, señales viales, árboles y aceras se ha realizado con software comercial, y para registros y edificios con los algoritmos propuestos. Las ratios de corrección y completitud, y la precisión geométrica se han calculado en las diferentes áreas urbanas. Los mejores resultados se han conseguido para las farolas, señales y bordillos, independientemente de la altura de los edificios. La peor ratio se obtuvo para los mismos elementos en áreas peri-urbanas, debido a la vegetación. Resultados opuestos se han conseguido en la detección de árboles. El coste económico y en tiempo de la metodología propuesta resulta inferior al de métodos tradicionales. Lo cual demuestra el gran potencial y eficiencia de la tecnología LiDAR móvil para la actualización cartografía de referenciaPostprint (published version