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Schuurmans, Juul (author)
Inadvertent bird nest destruction by autonomous mowing machines poses significant threats to the breeding success of meadow birds. Drone-based detection methods represent the current state-of-the-art for bird nest localization to attain mower circumvention. However, they only identify 80% of bird nests with average localization error of 3.344...
master thesis 2023
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Hoek, Tobias (author)
A scenario-based testing approach can reduce the time required to obtain statistically significant evidence of the safety of Automated Driving Systems (ADS). Identifying these scenarios in an automated manner is a challenging task. Most methods on scenario classification do not work for complex scenarios with diverse environments (highways,...
master thesis 2023
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de Leeuw, Wouter (author)
VPR describes a task where an agent (e.g., a robot) attempts to recognize its current location by comparing the incoming visual data from its sensor(s) (query images), usually a camera, to geotagged reference images. Both query and reference images are described using a feature extractor, and the query descriptor is matched to its closest...
master thesis 2023
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Şabanoğlu, Mahir (author)
An event-based camera enables capturing a video at a high temporal resolution, high dynamical range, reduced power consumption and minimal data bandwidth while the camera has minimal physical dimensions compared to a frame-based camera with the same vision properties. The limiting factor, however, of an event-based camera is the spatial...
master thesis 2023
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Kemmeren, Anne (author)
This thesis proposes a novel algorithm, Wi-Closure, to improve computational efficiency and robustness of map matching in multi-robot SLAM. Current state-of-the-art techniques connect maps with inter-robot loop closures, that are usually found through place recognition. Wi-Closure decreases the computational overhead of these approaches by...
master thesis 2022
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van Driel, Pieter (author)
This thesis research proposes a new method for a controlling an agricultural robot using computer vision. The robot has to follow and simultaneously reel in a hose, which lies on a grass field. The hose that has to be followed, is attached to the robot itself. The trajectory of the hose is captured by a monocular camera and is extracted from the...
master thesis 2022
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POLYA RAMESH, CHINMAY (author)
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...
master thesis 2022
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Looman, Danny (author)
Underwater position estimation is challenging due to the absence of Global Navigation Satellite System (GNSS) signals. Underwater vehicles are typically equipped with a Doppler Velocity Log (DVL) that measures the velocity relative to the seafloor. Aside from the velocity, the DVL also measures the range of each of the four beams. When compared...
master thesis 2022
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Ni, Ying-Chuan (author)
Adaptive Cruise Control (ACC) relieves human drivers’ tasks by taking over the control of the throttle and braking of the vehicles automatically. However, it has been demonstrated in many empirical studies that current production ACC systems fail to guarantee string stability. It is believed that if vehicles can take the longitudinal dynamics...
master thesis 2022
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Haifawi, Hani (author)
Drone detection and tracking systems are nowadays a requirement in most public, private and political events, because of the increasing risk of unintentional or malicious misuse of these platforms. Moreover, in order to ensure adequate protection, full spatial coverage is a must for every such system. However, the research literature focuses on...
master thesis 2022
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de Rijk, Philip (author)
Knowledge Distillation (KD) is a well-known training paradigm in deep neural networks where knowledge acquired by a large teacher model is transferred to a small student. KD has proven to be an effective technique to significantly improve the student's performance for various tasks including object detection. As such, KD techniques mostly rely...
master thesis 2022
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Tak, Seger (author)
Pedestrian trajectory prediction is essential for developing safe autonomous driving systems. Such trajectories depend on various contextual cues, among which surrounding objects. <br/><br/>This work proposes the first pedestrian trajectory prediction method in the 2D on-board domain that models interactions between the pedestrian and...
master thesis 2022
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Dirks, Rutger (author)
For an Autonomous Vehicle (AV) to traverse safely in traffic, It is vital it can anticipate the behavior of surrounding traffic participants using motion prediction. Current motion prediction approaches can be categorized into object-centered and object-agnostic methods and are primarily based on deep learning. The former relies on a human...
master thesis 2022
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Arunmoli, Karthik Arvind (author)
Learning from demonstration is a technique where the robot learns directly from humans. It can be beneficial to learn from humans directly because humans can easily demonstrate complex behaviors without being experts in demonstrating required tasks. However, it can be challenging to gather large amounts of data from humans because humans often...
master thesis 2021
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Wiersma, Mark (author)
Automated bin-picking is a difficult task that requires solving multiple robotic vision problems including object detection and grasp proposal generation. Current methods use deep learning to approach each of the vision problems of bin-picking separately with the main focus on generating the grasp proposals. For grasp proposal generation, neural...
master thesis 2021
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Patil, Sandeep (author)
Lane detection represents a fundamental task for automated/autonomous vehicles. Current lane detection methods do not provide the versatility of real-time performance, robustness,and accuracy required for real-world scenarios. The reasons include lack of computing power while being portable and inability to observe the continuity and structure...
master thesis 2021
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van Tilburg, Floris (author)
Suction based robotic actuators have potential for the bin-picking industry, but are currently not usable due the needed speed, accuracy and ability to handle novel and adversarial objects. An evaluation of the state of the art grasp pipeline developed by Mahler et al. [1] for detecting grasps on novel objects lead us to split the problem of...
master thesis 2021
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Wu, Yen-Lin (author)
3D human pose estimation is a widely researched computer vision task that could be applied in scenarios such as virtual reality and human-robot interaction. With the lack of depth information, 3D estimation from monocular images is an inherently ambiguous problem. On top of that, unrealistic human poses have been overlooked in the majority of...
master thesis 2021
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WANG, CHENXU (author)
Least Squares Support Vector Machines (LS-SVMs) are state-of-the-art learning algorithms that have been widely used for pattern recognition. The solution for an LS-SVM is found by solving a system of linear equations, which involves the computational complexity of O(N^3). When datasets get larger, solving LS-SVM problems with standard methods...
master thesis 2021
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Bosland, Liam (author)
A common problem in robotics is the simultaneous localization and mapping (SLAM) problem. Here, a robot needs to create a map of its surroundings while simultaneously localizing itself in this map. An unknown environment is assumed. Traditionally, it has been approached through filtering solutions. This paradigm has shifted to pose graph...
master thesis 2021
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