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Architecture and Task Plan Co-Adaptation with Metaplan for Unmanned Underwater Vehicles

Zwanepol, Jeroen (author)

Unmanned Underwater Vehicles (UUVs) operate in complex environments and need to be able to adapt to sudden failures, or changes in the environment. To achieve autonomous operation, UUVs must have the ability to self-adapt in such cases. To effectively handle component failures and unexpected events, self-adaptation must be applied to both the...

master thesis 2023

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Task-specific object grasps using primitive shapes and symbolic reasoning

Zwinkels, Stan (author)

In household and retail store environments, humans efficiently identify grasp regions of an object to perform everyday tasks. To enable robots to understand the requirements of a task and the properties of an object, a novel grasp framework, called the Shape Primitive and Reasoning Grasping Engine (SPaRGE), is proposed in this thesis. SPaRGE...

master thesis 2023

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Robotic Packaging Optimization with Reinforcement Learning and Real-World Data

Drijver, Eveline (author)

Intelligent manufacturing has become increasingly important in the food packaging industry due to the growing demand for enhanced productivity and flexibility while minimizing waste and lead times. This work explores the integration of such manufacturing in automated secondary robotic food packaging solutions that transfer food products into...

master thesis 2023

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Controlling the estimation bias in deep reinforcement learning problems with sparse rewards: Towards robust robotic object manipulation learning

Varga, Roland (author)

Many recent robot learning problems, real and simulated, were addressed using deep reinforcement learning. The developed policies can deal with high-dimensional, continuous state and action spaces, and can also incorporate machine-generated or human demonstration data. A great number of them depend on state-action value estimates, especially the...

master thesis 2023

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Developing a high-performance patient-to-image registration system for robotic cochlear implant surgery: Through the human-robot interaction-focused design method leading to a multi-modal, multi-feedback admittance control, touch-based pair-point bone-anchored fiducial registration and its performance measured in accuracy, workload, usability and trust

Halman, Susanna (author)

This thesis presents the research to design a successful high-accuracy, sub-millimetric registration method for an autonomous robot equipped to drill bone for cochlear implant (CI) surgery. Its performance, and thus success, is measured in accuracy, workload, usability and trust. While state-of-the-art (STOTA) research lacks the inclusion of...

master thesis 2023

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Controlling grip force by maintaining a constant frictional safety margin to improve robotic grasping

Langens, Coco (author)

Manipulating soft and fragile objects is a challenging task in robotic grasping. The key challenge for robotic grasping is to exert enough grip force to prevent slipping while being gentle enough to prevent damage to an object. Existing grippers used for processes like automatic harvesting of fruits, either apply excessive grip force leading to...

master thesis 2022

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Design validation of the MATE tendon-based passive device for post-stroke rehabilitation

Kieft, Levi (author)

Rehabilitation robots have been shown to be effective in post-stroke gait rehabilitation. However, these devices are usually expensive and suffer from high inertia which decreases transparency. The Minimally Actuated Tendon-based exercise Environment (MATE) is a tendon-based rehabilitation device, designed to be cost-effective and minimize...

master thesis 2022

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Learning dynamic models of soft manipulators via physics-inspired neural networks

Liu, Jingyue (author)

Soft robots are made of compliant materials, which increase their flexibility but also presents modeling challenges. The difficulty mainly comes from material nonlinearity, infinite degrees of freedom, uncertain parameters, and complex calculations. This project uses physics-inspired neural networks to solve the last two problems. Based on the...

master thesis 2022

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Robotic gripper for calli transfer: The design and development of a robotic gripper to automate calli transfer to improve the quality and quantity of plant regeneration

Konijnenberg, Thom (author)

During the transfer of calli in plant regeneration, the repetitive work of pick and placement of calli in new agar is still done by human operators. This process can be automated to eliminate labour-intensive work. The thesis focuses on the development of a robotic gripper to automate the transfer of calli. To be able to grip calli, first its...

master thesis 2022

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Driveability predictions in vibratory pile driving: A comparison of various machine learning approaches and the traditional model

Hazewinkel, Annabel (author)

Pile driving is a widely used technique for the construction of buildings and infrastructure. A popular technique is to vibrate the pile into the sediment. However, since building sites are increasingly being located in metropolitan areas, there is a growing concern about the environmental impact that vibrations may cause during driving....

master thesis 2022

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Safe Patient-Led Shoulder Rehabilitation with Biomechanical Model Integrated Collaborative Robot System

Balvert, Stephan (author)

In this work, we propose a method for monitoring and management of rotator-cuff tendon strains in human-robot collaborative physical therapy for rotator cuff rehabilitation. The proposed approach integrates a complex offline biomechanical model with a collaborative, industrial robot arm and an impedance controller. The model is used for...

master thesis 2022

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Legible Grasping with Teleoperated Learning from Demonstration

van Beem, Marnix (author)

State-of-the-art object grasping with 7-DOF robotic manipulators requires joint configuration planning methods in order to provide position control of the end-effector. These motion planners are able to calculate a motion plan to execute a safe grasp, while taking environmental constraints into account. In human-robot...

master thesis 2022

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A time-reversed model identification approach to time series forecasting

Sibeijn, Max (author)

In this thesis, I introduce a novel model identification approach to time series forecasting. For linear stationary processes, such as AR processes, the direction of time is independent of the model parameters. By combining theoretical principles of time-reversibility in time series with conventional modeling approaches such as information...

master thesis 2021

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Single Shot Learning of the Stiffness Distribution of a Soft Object

Besselaar, Lars (author)

With robotics rapidly expanding towards new user-oriented applications, such as agriculture, households, and classrooms, new tasks and new requirements arise. One of the ongoing and unsolved problems that comes with the unpredictable new environments robots find themselves in, is soft object manipulation. Without assuming the handled object to...

master thesis 2021

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Interactive Imitation Learning for Force control: Position And Stiffness Teaching with Interactive Learning

Lander, Niels (author)

To generalize the use of robotics, there are a few hurdles still to take. One of these hurdles is the programming of the robots. Most robots on the market today employ position control, with a set of controller parameters tuned by an expert. This programming is quite expensive, only suited for a single task, in a single configuration, and not...

master thesis 2021

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Discrete state-space active inference in nonstationary environments

Pancham, Naresh (author)

Active inference is a neuroscientific theory, which states that all living systems (e.g. the human brain) minimize a quantity termed the free energy. By minimizing this free energy, living systems keep an accurate representation of the world in their internal model (learning), are provided with an optimal way of acting on the world (action...

master thesis 2021

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Bayesian Deep Learning for Dynamic System Identification

Chahine, Ibrahim (author)

System identification is a mature field in physical sciences and an emerging field in social sciences, with a vast range of applications. Nevertheless, it remains of great focus in academia. The main challenge is the efficient use of data to generate good model fits. System identification involves multi-disciplinary techniques from statistical,...

master thesis 2021

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Reducing settling time in high acceleration applications of macro scale robotic manipulators with dynamic balancing

Zomerdijk, Matthijs (author)

High accelerations in unbalanced robotic manipulators can induce significant base vibrations, which reduces precision and increases settling time. These vibrations are caused by fluctuating reaction forces and reaction moments exerted on the base by the manipulator. Dynamic balancing eliminates these fluctuations and therefore improves...

master thesis 2020

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Visual Feedback for Haptic Assisted Teleoperation of an Industrial Robot: With Dross Removal as a Use Case

van den Berg, Alex (author)

Haptic assistance (HA) has been shown to be useful in a wide variety of applications by providing the benefits of automation while keeping the human in the loop. In recent years, providing additional visual feedback has been found to provide benefits to HA interfaces by complementing their advantages and mitigating their weaknesses. However, the...

master thesis 2020

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Improving safety and performance for mobile robot navigation using self-adaptation in retail environments

Wijkhuizen, Jasper (author)

There is a growing demand for autonomous mobile robots in industry. The robots need to solve, among other things, the problem of navigation. Since the robots operate in semi-structured and (partially) unknown environments, the local path planning sub-problem has received a lot of attention from researchers. The result is a large variety of...

master thesis 2020