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Real-time reconstruction of indoor ground surfaces in occluded environments filled with smoke based on point clouds obtained using LiDAR

Wiers, Christiaan (author)

With the current transition towards renewable and high-tech solutions, the world is becoming increasingly complex. Consequently, the challenges faced by firefighters also intensify. For that reason, firefighting robots are rising in popularity despite being far from perfect. An important area of improvement is the perception capabilities of...

master thesis 2024

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Pedestrian Interaction Modelling: Leveraging Trajectory Prediction for Belief Representation

Weinans, Tom (author)

Autonomy in traffic (e.g., autonomous vehicles) could potentially benefit mobility, safety, accessibility and sustainability. However, the realisation of these advancements is highly dependent on how effective these autonomous vehicles interact with vulnerable road users such as pedestrians. Before we can understand how pedestrians will interact...

master thesis 2024

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Experimental Validation of Model-Based Control Methods for Shape Regulation in Soft Robots

Bhatti, Ghanishtha (author)

Soft robots are characterized by compliant elements that introduce heightened kinematic complexity compared to their rigid counterparts. Such systems, with infinite degrees of freedom, are inherently underactuated, making precise real-time shape regulation a challenging task. Model-based controllers, utilizing tractable reduced-order modelling...

master thesis 2024

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Learning Task Parameterised Dynamical Systems with Gaussian Process Regression and Classification

Ramírez Montero, Mariano (author)

Recent research has shown that a Learning from Demonstration (LfD) approach is useful for teaching robots flexible skills efficiently, and it opens the possibility for non-expert users to program these skills. When learning from demonstration data, learning frameworks should learn representations that are flexible and can generalize to unseen...

master thesis 2023

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Grasp recognition with spatiotemporal deep learning and proximity sensors in transradial prostheses

van den Berg, Jasper (author)

The traumatic loss of a hand is a horrific experience usually followed by significant psychological, functional and rehabilitation challenges. Even though much progress has been made in the past decades, the prosthetic challenge of restoring the human hand functionality is still far from being achieved. Autonomous prosthetic hands showed...

master thesis 2023

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Telerehabilitation of a Exoskeleton-haptic device System: Design and Evaluation on Stability and Transparency

Korzilius, Nikki (author)

While the presence and demand of robotic rehabilitation devices are rising, not many studies have been performed on haptic communication/ telerehabilitation with these devices. Despite therapists' desire to have the possibility to remain in the loop when their patients are performing exercises. This study aims to provide a telerehabilitation...

master thesis 2023

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Multi-Modal MPPI and Active Inference for Reactive Task and Motion Planning

ZHANG, Frankie (author)

Task and Motion Planning (TAMP) has progressed significantly in solving intricate manipulation tasks in recent years, but the robust execution of these plans remains less touched. Particularly, generalizing to diverse geometric scenarios is still challenging during execution. In this work, we propose a reactive TAMP method to deal with...

master thesis 2023

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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