Searched for: contributor:"Kober, J. (mentor)"
(1 - 12 of 12)
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Valletta, P. (author)
Interactive machine learning describes a collection of methodologies in which a human user actively participates in a novice agent’s learning process, through providing corrective or evaluate feedback or demonstrative actions. A primary assumption in these methods is that user input is at worst nearoptimal, however a realistic set of...
master thesis 2020
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Olsthoorn, R.M. (author)
The use of robotic systems outside the branch of tasks currently common in industry requires the development of novel intelligent control methods. In this thesis we will aim to improve on a recent machine learning method known as active reward learning. This method is able to teach a robotic system a task using human expert ratings on...
master thesis 2017
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Kathmann, Y. (author)
This thesis aims to combine visual data and distance measurements from a Laser Range Finder (LRF) to recognise the presence of humans. The data from the LRF is used to find regions of interest in order to reduce the load on the visual data analysis. Deep learning convolutional neural networks have shown incredible results on visual recognition...
master thesis 2017
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Marck, N.L.D. (author)
A recent trend in robotics is aimed at the cooperation between human and robot. This has led to an increased development of collaborative robot manipulators. Typical characteristics of collaborative robots are their user-friendly and lightweight design, innovative compliant mechanics, the implementation of various safety features and advanced...
master thesis 2017
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Mus, D.A. (author)
In order to interact with environments and appliances made for humans, robots should be able to manipulate a large variety of objects and appliances in human environments. When having experience with manipulating a certain object or appliance, a robot should be able to generalize this behaviour to novel, but similar objects and appliances. When...
master thesis 2017
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Zhang, X. (author)
: Tooth extraction is one of the most common procedures in oral surgery. However, it is complicated as well as not fully understood. Different teeth have different structures and strengths. Even teeth of the same type differ depending on ages, genders, races, and other reasons affecting its integrity. During the procedure, the properties of the...
master thesis 2016
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van Spaandonk, V. (author)
Modern robotic systems are increasingly expected to interact with unstructured and unpredictable environments. This has reiterated the importance of sophisticated reasoning and adaptive motor skill learning. Although low-level methodologies for sensorimotor control have been relatively well studied, constrained motion for robotic manipulators in...
master thesis 2016
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van der Wijden, R. (author)
New flexible teaching methods for robotics are needed to automate repetitive tasks that are currently still done by humans. For limited batch sizes, it is too expensive to teach a robot a new task (Smith & Anderson, 2014). Ideally, such flexible robots can be taught a new task by a non-expert. A non-expert is a person who knows the task the...
master thesis 2016
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Munk, J. (author)
In control, the objective is to find a mapping from states to actions that steer a system to a desired reference. A controller can be designed by an engineer, typically using some model of the system or it can be learned by an algorithm. Reinforcement Learning (RL) is one such algorithm. In RL, the controller is an agent that interacts with the...
master thesis 2016
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Feirstein, D.S. (author)
Reinforcement learning is a powerful tool to derive controllers for systems where no models are available. Particularly policy search algorithms are suitable for complex systems, to keep learning time manageable and account for continuous state and action spaces. However, these algorithms demand more insight into the system to choose a suitable...
master thesis 2016
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Zhu, J. (author)
The thesis contributes to the pre-collision strategies of robot manipulators by proposing a real-time implementable collision avoidance scheme. The collision is avoided by a braking controller that is activated by a braking trajectory predictor. The predictor provides distances of the end-effector to the object/human in the environment and...
master thesis 2015
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Van der Laan, T.A. (author)
The works [Volodymyr et al. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602, 2013.] and [Volodymyr et al. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 2015.] have demonstrated the power of combining deep neural networks with Watkins Q learning. They introduce deep Q networks ...
master thesis 2015
Searched for: contributor:"Kober, J. (mentor)"
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