Compressing YOLOv7

In the literature, neural network compression can significantly reduce the number of floating-point operations (FLOPs) of a neural network with limited accuracy loss. At the same time, it is common to manually design smaller networks instead of using modern compression techniques. This thesis will compare the two approaches for the object...

Factor graphs for inventory label scanning in warehouse

A key important part of a warehouse operation is to keep track of the products in the warehouse. Traditionally, handheld scanners are used to scan the products to perform a stock count. The advancements in robotics have paved the way for new technologies that can improve the scanning process. This work shows how prior knowledge and warehouse...

Reduce, Reuse, Recycle: On exploration of solution reuse in VRPTW

Solving routing problems efficiently is instrumental in minimizing operational costs in logistics. These routing problems are hard to solve and often take a lot of time to find a good solution. In this thesis, we present a methodology that tackles the challenge of efficiently solving recurring instances of the Vehicle Routing Problem with Time...

Multi-Sensor Fusion of IMU, LIDAR and Wheel Encoders: Towards Tightly-Coupled Odometry

Loop Robots develops and operates the next generation of fully autonomous disinfection robots in hospitals and healthcare settings. Accurate localization is essential in order to navigate reliably and effectively disinfect the tight hallways and corners of a patient room, operating room, or intensive care unit in a hospital. Odometry, or dead...

Particle Inspection: Modules of the Visual Particle Inspection Subsystem; Detection of Particle Contamination in Medicine Containers with Novel Solutions for Background Subtraction and Segmentation, Classification, and Tracking

Visual inspection of liquid medicine containers for contamination and defects is mandatory and crucial to ensure their safety for injection. This document presents research and development of three modules of the Visual Particle Inspection Subsystem (VPIS), an automatic inspection subsystem with the task of detecting and classifying particle...

Smooth-Trajectron++: Augmenting the Trajectron++ behaviour prediction model with smooth attention

Understanding traffic participants’ behaviour is crucial for predicting their future trajectories, enabling autonomous vehicles to better assess the environment and consequently anticipate possible dangerous situations at an early stage. While the integration of cognitive processes and machine learning models has demonstrated promise in various...

Simple Online Visual Object Tracker Fusion based on Distributed Kalman Filtering

Tracker-level fusion (TLF) is recognized as an effective approach to comprehensively improve visual object tracking performance by combining the capabilities of multiple baseline trackers. Although there is considerable interest in TLF, there are still challenges related to insufficient understanding, high cost, and unstable performance that...

Enriching Diversity of Synthetic Images for Person Detection

Camera-based patient monitoring is undergoing rapid adoption in the healthcare sector with the recent COVID-19 pandemic acting as a catalyst. It offers round-the-clock monitoring of patients in clinical units (e.g. ICUs, ORs), or at their homes through installed cameras, enabling timely, pre-emptive care. These are powered by Computer Vision...

Significance of Static Backgrounds for Video Object Detection

Video Object Detectors (VID) are used in various applications such as surveillance, inspection, etc. Often in these applications there exists a spatial area of interest and a static background. The static backgrounds remain constant throughout the video sequence in the training data establishing an undesirable correlation with the moving object...

SliceNet: Street-to-Satellite Image Metric Localization using Local Feature Matching

This work addresses visual localization for intelligent vehicles. The task of cross-view matching-based localization is to estimate the geo-location of a vehicle-mounted camera by matching the captured street view image with an overhead-view satellite map containing the vehicle's local surroundings. This local satellite view image can be...

Can PredNet predict time-series to improve the generalization process?

This thesis is inspired by Active Inference to contribute to its improvement in the Robotics work field. However, the results and applications of this thesis are useful in a broader perspective, namely in any field that makes use of derivatives and the forecasting of a time-series signal. The goal of this study is to determine a new approach for...