Searched for: contributor%3A%22Kober%2C+J.+%28mentor%29%22
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Keijzer, Alexander (author)
Experience replay for off-policy reinforcement learning has been shown to improve sample efficiency and stabilize training. However, typical uniformly sampled replay includes many irrelevant samples for the agent to reach good performance. We introduce Action Sensitive Experience Replay (ASER), a method to prioritize samples in the replay buffer...
master thesis 2023
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Du, Zheyu (author)
Robot dexterous manipulation research has drawn more attention in recent years since the development of various learning methods makes it possible for robots to achieve dexterity at the human level. Many attempts have been made to integrate human knowledge into Reinforcement Learning (RL) processes for faster learning speed and better...
master thesis 2023
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Sun, Jianyong (author)
Learning from Demonstration (LfD) aims to learn versatile skills from human demonstrations. The field has been gaining popularity since it facilitates transferring knowledge to robots without requiring much expert knowledge. During task executions, the robot motion is usually influenced by constraints imposed by environments. In light of this,...
master thesis 2022
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Qiu, Yulei (author)
Deformable Object Manipulation (DOM) is an important field of research as it contributes to practical tasks such as cloth handling, cable routing, surgical operation etc. The sensing in DOM is now considered as one of the major challenges in robotics due to the complex dynamics and high degree of freedom of deformable objects. One challenge is...
master thesis 2022
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van der Lely, Lars (author)
Over nine billion people will have to be fed fresh and healthy food in 2050 according to United Nations. This puts pressure on the horticulture sector, responsible for a large portion of the world’s food production. The literature has shown that automatic optimal control algorithms are able to make better use of resources and can even outperform...
master thesis 2022
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Bornhijm, Bram (author)
Whilst the extraction of teeth (exodontia) remains one of the oldest and most performed surgeries on earth, very little is understood about the procedure itself. Especially in the area of the required movements, torques and forces to remove specific teeth and how these interact with existing tissue. This knowledge gap has been hypothesized to...
master thesis 2022
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DU, YURUI (author)
In recent years, imitation learning (IL) has been widely used in industry as the core of autonomous vehicle (AV) planning modules. However, previous work on IL planners shows sample inefficiency and low generalisation in safety-critical scenarios, on which they are rarely tested. As a result, IL planners can reach a performance plateau where...
master thesis 2022
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Bay, Besim (author)
Grocery e-commerce has been rapidly increasing in recent years, posing a new challenge for retailers as groceries, unlike other goods, have a limited shelf life. Thus, customers expect their orders to arrive quickly and undamaged. Currently, most processes between a customer placing an order and the delivery are performed manually in a warehouse...
master thesis 2022
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de Lange, Rudy (author)
This thesis proposes the novel Behaviour Tree Update Framework (BTUF) for the initial construction and continuous incremental adaptation of Behaviour Trees (BTs) for applications in Learning from Demonstration (LfD) frameworks to create complex robot behaviours associated with Activities of Daily Living (ADL) without requiring the user to have a...
master thesis 2022
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Haasdijk, Annemarijn (author)
master thesis 2022
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Uitendaal, Sven (author)
While robots execute many tasks where physical interaction with the environment is required, it is still challenging to control a robot that deliberately makes contact at a non-zero velocity, especially with multiple contact points that are impacted simultaneously.<br/>When there is a mismatch between planned and actual impact time, the robot...
master thesis 2022
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Boonstra, Dirk-Jan (author)
Tactile sensing provides crucial information about the stability of a grasped object by a robotic gripper. Tactile feedback can be used to predict slip, allowing for timely response to perturbations and to avoid dropping objects. Tactile sensors, included in robotic grippers, measure vibrations, strain or shearing forces which are produced by...
master thesis 2022
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Lopez Bosque, Irene (author)
Interactive imitation learning refers to learning methods where a human teacher interacts with an agent during the learning process providing feedback to improve its behaviour. This type of learning may be preferable with respect to reinforcement learning techniques when dealing with real-world problems. This fact is especially true in the case...
master thesis 2021
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Avaei, Armin (author)
Humans often demonstrate diverse behaviours due to their personal preferences, for instance related to their individual execution style or personal margin for safety. In this paper, we consider the problem of integrating such preferences into planning of trajectories for robotic manipulators. We first learn<br/>reward functions that represent...
master thesis 2021
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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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ter Kuile, David (author)
As robots are becoming a more integral part in our daily lives, it is important to ensure they work in a safe and efficient manner. A large part of perceiving the environment is done through robot vision. Research in computer vision and machine learning lead to great improvements in the past decades and robots are able to outperform humans on...
master thesis 2021
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TSAI, CHIA-YU (author)
Deformable objects manipulation (DOM) is largely considered an open problem in robotics. The complexity stems from the high degrees of freedom and nonlinear nature of the object configurations. In this thesis, we consider placing and flattening tasks for cloth-like objects. We propose a practical framework to place a cloth on a surface based on...
master thesis 2021
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Suresh Kumar, Lalith Keerthan (author)
In this thesis, we propose a method titled "Task Space Policy Learning (TaSPL)", a novel technique that learns a generalised task/state space policy, as opposed to learning a policy in state-action space, from interactive corrections in the observation space or from state only demonstration data. This task/state space policy enables the agent to...
master thesis 2021
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Harleman, Bram (author)
Research has shown that GLOSA systems can help reduce the emission of $CO_2$ by motor vehicles and improve flow on urban road networks. However, existing GLOSA systems only work in combination with a limited selection of Traffic Signal Controllers (TSCs) and therefore have not been widely implemented. This research describes and evaluates the...
master thesis 2021
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D'Elia, Evelyn (author)
Designing controllers for complex robots is not an easy task. Often, researchers hand-tune controllers for humanoid robots, but this is a time-consuming approach that yields a single controller which cannot generalize well to varied tasks. This thesis presents a method which uses the NSGA-II multi-objective optimization (MOO) algorithm with...
master thesis 2021
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