Searched for: subject%3A%22Autonomous%22
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Kuhm, T.I. (author)
doctoral thesis 2024
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Enting, Marnix (author)
Neural Radiance Fields (NeRFs) have showcased remarkable effectiveness in capturing complex 3D scenes and synthesizing novel viewpoints. By inherently capturing the entire scene in a compact representation, they offer a promising avenue for applications such as simulators, where efficient storage of real-world data, fast rendering and dynamic...
master thesis 2024
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Yin, Lanke (author)
This work introduces a novel training strategy for Gaussian Process (GP) models aimed at improving their predictive accuracy and uncertainty quantification capabilities over extended prediction horizons. This improvement is highly relevant for applications in model predictive control (MPC) in the autonomous driving domain. Learning-based MPC...
master thesis 2024
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Brodnevskaya, Kristina (author)
In the face of accelerating urbanization and the consequent surge in housing demands, particularly in European capitals, Copenhagen is at the forefront of adopting innovative urban development strategies. One such strategy is the conceptualization and eventual realization of Lynetteholm, an artificial island designed to mitigate housing...
master thesis 2024
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Bink, Kiki (author)
Facing the critical challenge of reducing greenhouse gas (GHG) emissions in the maritime industry, this thesis explores the potential of smart control systems using Reinforcement Learning (RL) for autonomous sailing. Traditional controls for sailing fall short in navigating the complex, dynamic conditions of maritime environments. RL has shown...
master thesis 2024
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Hazelaar, Sander (author)
New insights into the landing behavior of bumblebees show an adaptive strategy where the optical flow expansion of the landing target is step-wise regulated. In this article, the potential benefits of this approach are studied by replicating the landing experiment with a quadrotor. To this end, an open-loop switching method is developed,...
master thesis 2024
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Bestebreur, Timon (author)
The versatility of the internet enables many applications that play an increasingly bigger role in our society. However, users have little control over the route that their internet traffic takes, which prevents them from controlling who sees their packets and how their traffic is handled. Researchers have proposed an extension to the internet,...
master thesis 2024
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Bolscher, Thijs (author)
As the Moon reemerges as a renewed fronteer in space exploration, the Lunar Zebro project proposes to deploy a swarm of miniature rovers for efficient lunar surface exploration. One of their goals is to leverage recent advancements in deep learning and AI-accelerating hardware, in conjunction with Commercial Off-The-Shelf technologies and the...
master thesis 2024
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Yildiz, Haydar (author)
master thesis 2024
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Trip, Kenrick (author)
With the introduction of autonomous vehicles on public roads, their performance in emergency situations has become a strong focus. Collision Imminent Control (CIC) concerns the planning and control of aggressive evasive maneuvers for collision avoidance of automated vehicles. CIC is implemented using adaptive Nonlinear Model Predictive Control ...
master thesis 2024
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Zwanenburg, Andreas (author)
These days, people see more and more applications for drones, including monitoring rainforests to protect plant and animal species. However, drones face challenges when navigating through the dense and cluttered vegetation of the forest. These environments necessitate advanced autonomous detection and navigation to make the drone traverse...
master thesis 2024
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Homola, Marek (author)
In the rapidly evolving aviation sector, the quest for safer and more efficient flight operations has historically relied on traditional Automatic Flight Control Systems (AFCS) based on high-fidelity models. However, such models not only incur high development costs but also struggle to adapt to new, complex aircraft designs and unexpected...
master thesis 2024
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CHEN, XI (author)
In autonomous driving, environmental perception, crucial for navigation and decision-making, depends on integrating data from multiple sensors like cameras and LiDAR. Camera-LiDAR fusion combines detailed imagery with precise depth, improving environmental awareness. Effective data fusion requires accurate extrinsic calibration to align camera...
master thesis 2024
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Bērmans, Boriss (author)
Detecting nearby vehicles involves utilizing data from various sensors installed on a car as it moves. Common sensors for identifying nearby vehicles include LiDAR, cameras, and RADAR. However, all of these sensors suffer from the same issue -- they cannot detect an approaching vehicle that is not yet visible. Hence, this thesis explores the...
master thesis 2024
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He, P. (author), Jin, Jian Gang (author), Trépanier, Martin (author), Schulte, F. (author)
The burden of first-mile connection to public transit stations is a key barrier that discourages riders from taking public transportation. Public transit agencies typically operate a modest fleet of vehicles to provide first-mile services due to the high operating costs, thus failing to adequately meet the first-mile travel demands,...
journal article 2024
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Wang, Zhimian (author), An, Kun (author), Correia, Gonçalo (author), Ma, Wanjing (author)
Anticipating the forthcoming integration of shared autonomous vehicles (SAVs) into urban networks, the imperative of devising an efficient real-time scheduling and routing strategy for these vehicles becomes evident if one is to maximize their potential in enhancing travel efficiency. In this study, we address the problem of jointly...
journal article 2024
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Damsgaard, Hans Jakob (author), Grenier, Antoine (author), Katare, D. (author), Taufique, Zain (author), Shakibhamedan, Salar (author), Troccoli, Tiago (author), Chatzitsompanis, Georgios (author), Kanduri, Anil (author), Ding, Aaron Yi (author)
Recent advancements in hardware and software systems have been driven by the deployment of emerging smart health and mobility applications. These developments have modernized the traditional approaches by replacing conventional computing systems with cyber–physical and intelligent systems combining the Internet of Things (IoT) with Edge...
review 2024
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Li, G. (author), Li, Zirui (author), Knoop, V.L. (author), van Lint, J.W.C. (author)
Resolving predicted conflicts is vital for safe and efficient autonomous vehicles (AV). In practice, vehicular motion prediction faces inherent uncertainty due to heterogeneous driving behaviours and environments. This spatial uncertainty increases non-linearly with prediction time horizons, leading AVs to perceive more road space occupied by...
journal article 2024
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Bai, Chengchao (author), Yan, Peng (author), Piao, Haiyin (author), Pan, W. (author), Guo, Jifeng (author)
This article explores deep reinforcement learning (DRL) for the flocking control of unmanned aerial vehicle (UAV) swarms. The flocking control policy is trained using a centralized-learning-decentralized-execution (CTDE) paradigm, where a centralized critic network augmented with additional information about the entire UAV swarm is utilized...
journal article 2024
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Casao, S. (author), Serra Gomez, A. (author), Murillo, Ana C. (author), Böhmer, J.W. (author), Alonso-Mora, J. (author), Montijano, Eduardo (author)
Smart cameras are an essential component in surveillance and monitoring applications, and they have been typically deployed in networks of fixed camera locations. The addition of mobile cameras, mounted on robots, can overcome some of the limitations of static networks such as blind spots or back-lightning, allowing the system to gather the...
journal article 2024
Searched for: subject%3A%22Autonomous%22
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