Global ETD Search

401	Asynchronous Event-Feature Detection and Tracking for SLAM Initialization Ta, Tai January 2024 (has links) Traditional cameras are most commonly used in visual SLAM to provide visual information about the scene and positional information about the camera motion. However, in the presence of varying illumination and rapid camera movement, the visual quality captured by traditional cameras diminishes. This limits the applicability of visual SLAM in challenging environments such as search and rescue situations. The emerging event camera has been shown to overcome the limitations of the traditional camera with the event camera's superior temporal resolution and wider dynamic range, opening up new areas of applications and research for event-based SLAM. In this thesis, several asynchronous feature detectors and trackers will be used to initialize SLAM using event camera data. To assess the pose estimation accuracy between the different feature detectors and trackers, the initialization performance was evaluated from datasets captured from various environments. Furthermore, two different methods to align corner-events were evaluated on the datasets to assess the difference. Results show that besides some slight variation in the number of accepted initializations, the alignment methods show no overall difference in any metric. Overall highest performance among the event-based trackers for initialization is HASTE with mostly high pose accuracy and a high number of accepted initializations. However, the performance degrades in featureless scenes. CET on the other hand shows mostly lower performance compared to HASTE. Visual SLAM SLAM Traditional cameras event camera events neuromorphic camera silicon retina dynamic vision sensor Camera motion Illumination variation Rapid camera movement Visual quality degradation Challenging environments Search and rescue Event cameras Temporal resolution Dynamic range Event-based SLAM Asynchronous feature detectors Trackers Pose estimation accuracy Initialization performance Datasets Corner-event alignment HASTE tracker Pose accuracy Featureless scenes CET tracker Initialization acceptance Performance comparison Signal Processing Signalbehandling Robotics Robotteknik och automation Control Engineering Reglerteknik
402	Leveraging IoT Protocols : Integrating Palletization Algorithm with Flexible Robotic Platform Ferm Dubois, Mathias January 2024 (has links) This thesis explores the integration of IoT protocols to enhance supply chain efficiency and sustainability by developing a flexible automated system. The research covers the integration of a palletization optimizer with a flexible robotic platform, a project conducted in collaboration with OpiFlex and Linköping University. Flexibility and sustainability in production, particularly in the food and beverage industry, are critical yet challenging to achieve. This research addresses these challenges by proposing a system that aligns the output with customer needs by combining these technologies. The research employs a combination of case study and exploratory methodologies. The development approach synthesizes elements from Set-Based Design, Point-Based Design, and Agile development frameworks. The primary research questions focus on identifying the best system architecture for integrating the palletization optimizer with a lower-level automation platform and outlining the steps needed to transform this integration into a commercially viable product. The system includes the optimizer, capable of processing customer orders and configuring products on mixed output pallets, integrated with a flexible robotic system provided by OpiFlex. The work involved evaluating communication protocols, MQTT, OPC UA, and TCP/IP, and designing robust interactions and interfaces between the subsystems. The results demonstrate the system's architecture and interaction protocols. The thesis concludes with a discussion of the results in comparison to the application scenario and the standards consulted. The conclusion is that the chosen interface practices should remain largely intact but be re-developed using an OPC UA-based architecture. The main reasons for this are its support for both pub/sub and client-server models, increased security, and greater support for enterprise application integration. However, depending on the specific application, the downsides of OPC UA may outweigh its benefits. IoT IIoT CPS CPPS MAS Multi-Agent Systems Industrial Systems Integration IT/OT OPC UA MQTT Automation Palletization Algorithm Supply Chain Efficiency Flexibility Automated Flexibility Sustainable Supply Chain Food and Beverage Industry Industry 4.0 RAMI 4.0 3D Bin Packing Problem Loosely Coupled Integration Tightly Coupled Integration Trade-offs in System Design IoT Security Enterprise Application Integration Communication Protocols Computer and Information Sciences Data- och informationsvetenskap Elektroteknik och elektronik Robotics Robotteknik och automation
403	Revision of an artificial neural network enabling industrial sorting Malmgren, Henrik January 2019 (has links) Convolutional artificial neural networks can be applied for image-based object classification to inform automated actions, such as handling of objects on a production line. The present thesis describes theoretical background for creating a classifier and explores the effects of introducing a set of relatively recent techniques to an existing ensemble of classifiers in use for an industrial sorting system.The findings indicate that it's important to use spatial variety dropout regularization for high resolution image inputs, and use an optimizer configuration with good convergence properties. The findings also demonstrate examples of ensemble classifiers being effectively consolidated into unified models using the distillation technique. An analogue arrangement with optimization against multiple output targets, incorporating additional information, showed accuracy gains comparable to ensembling. For use of the classifier on test data with statistics different than those of the dataset, results indicate that augmentation of the input data during classifier creation helps performance, but would, in the current case, likely need to be guided by information about the distribution shift to have sufficiently positive impact to enable a practical application. I suggest, for future development, updated architectures, automated hyperparameter search and leveraging the bountiful unlabeled data potentially available from production lines. artificial neural networks machine learning deep learning connectionism pattern recognition machine learning automation image analysis information technology applied mathematics mathematical optimization information theory mathematical statistics mathematical models stochastic models probabilities chance approximations algorithms computer programs computer software signal processing high performance computing numerical methods high technology industries sustainable development artificiella neurala nätverk maskininlärning djup maskininlärning konnektionism mönsterigenkänning automatisering bildanalys informationsteknik tillämpad matematik optimering informationsteori statistisk inferens matematiska modeller stokastiska modeller sannolikhetskalkyl slumpen approximationer algoritmer datorprogram programvara signalbehandling högpresterande beräkningar numeriska metoder teknikutveckling maskinindustri högteknologisk industri maskinhandel skrothandel bärkraftig utveckling Robotics Robotteknik och automation Probability Theory and Statistics Sannolikhetsteori och statistik Other Computer and Information Science Annan data- och informationsvetenskap Signal Processing Signalbehandling

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