Searched for: subject%3A%22manipulator%22
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Bom, Alexander (author)
Drones are increasingly used nowadays, primarily for visual inspection tasks facilitated by onboard cameras. The field of aerial manipulation tries to expand the capabilities of drones by attaching a manipulator, enabling physical interaction. Unfortunately, the usability of aerial manipulators is hindered by disturbances resulting from the...
master thesis 2024
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Berjaoui Tahmaz, Amin (author)
This paper presents a hierarchical reinforcement learning framework for efficient robotic manipulation in sequential contact tasks. We leverage this hierarchical structure to sequentially execute behavior primitives with variable stiffness control capabilities for contact tasks. Our proposed approach relies on three key components: an action...
master thesis 2024
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Kok, Wouter (author)
In this master thesis, the development of an innovative gripper specifically designed for grasping the delicate peduncles of vine tomato trusses is presented. This research addresses a critical challenge in agricultural automation: efficiently and safely manipulating high-value crops without causing damage. The thesis begins with a comprehensive...
master thesis 2024
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Castro-Alonso, Juan C. (author), Ayres, Paul (author), Zhang, S. (author), de Koning, Björn B. (author), Paas, Fred (author)
Research on embodied cognition acknowledges that cognitive processing is tightly coupled with bodily activities and the environment. An important implication for education is that learning can be enhanced when the brain, body, and environment mutually influence each other, such as when making or observing human actions, especially those...
review 2024
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Atzampou, P. (author), Meijers, P.C. (author), Tsouvalas, A. (author), Metrikine, A. (author)
Current offshore wind turbine installation and positioning methods require mechanical equipment attached on the lifted components and human intervention. The present paper studies the development of a contactless motion compensation technique by investigating a magnetically controlled pendulum. The technique involves the interaction of a...
journal article 2024
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Klenk, M.B.O.T. (author)
Generative AI enables automated, effective manipulation at scale. Despite the growing general ethical discussion around generative AI, the specific manipulation risks remain inadequately investigated. This article outlines essential inquiries encompassing conceptual, empirical, and design dimensions of manipulation, pivotal for comprehending...
journal article 2024
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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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Dijkstra, Mathijs (author)
This thesis presents the conceptual development of an innovative parallel manipulator that leverages the beneficial attributes of parallel kinematic structures. These attributes include increased stiffness, uniform load distribution, and reduced moving mass, which are strategically incorporated into the design to enhance resource efficiency....
master thesis 2023
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Bessels, Koen (author)
This study investigated the human-robot interaction of three different augmented reality interfaces that enabled an operator to control a robot arm. The first control methods gives the operator complete manual control by moving a holographic object which the robot arm copies (Direct control). The second control method allows the operator to...
master thesis 2023
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Tiburzio, Seb (author)
In robotic manipulation of deformable objects, the continuum nature of the object state leads to prohibitively high degrees of freedom when traditional modelling techniques are applied, leading to much research focusing on approaches that avoid an explicit object model. However, without such a model the opportunities for long horizon planning...
master thesis 2023
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van den Bent, Luuk (author)
master thesis 2023
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van der Burg, Thijs (author)
Object pushing in robotics has numerous applications, but it often relies on room-bound object tracking systems such as Motion Capture (MoCap) for accurate object pose acquisition. Such systems limit the potential use scenarios, since they add complexity and cost and require expansion of the sensor infrastructure for expanding the operational...
master thesis 2023
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Bărbulescu, Liliana (author)
Robot manipulators are significantly more accurate than their human counterparts and enhance the repeatability of various tasks. However, manufactures still provide reduced information regarding the robot controller functions, typically affecting robots' predictability. Additionally, industrial examples show that system transparency could be...
master thesis 2023
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Brummelhuis, Martijn (author)
Aerial physical interaction opens the door for many operations at height to be automatised using aerial robots. This research presents a novel manipulator design mounted on a traditional quadrotor, which utilises both mechanical and software compliance to perform physical interaction on vertical walls and overhanging surfaces, such as those...
master thesis 2023
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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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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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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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Du, Zhe (author), Negenborn, R.R. (author), Reppa, V. (author)
The regulatory endorsement of the International Maritime Organization (IMO) and the support of pivotal shipping market players in recent years motivate the investigation of the potential role that autonomous vessels play in the shipping industry. As the complexity and scale of the envisioned applications increase, research works gradually...
review 2023
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Rahimi, A. Masie (author), Hardon, S.F. (author), Willuth, E. (author), Lang, F. (author), Haney, Caelan M. (author), Felinska, Eleni A. (author), Kowalewski, Karl Friedrich (author), Müller-Stich, Beat P. (author), Horeman, T. (author), Nickel, F. (author), Daams, Freek (author)
Introduction: Although robotic-assisted surgery is increasingly performed, objective assessment of technical skills is lacking. The aim of this study is to provide validity evidence for objective assessment of technical skills for robotic-assisted surgery. Methods: An international multicenter study was conducted with participants from the...
journal article 2023
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Spahn, M. (author), Wisse, M. (author), Alonso Mora, J. (author)
Optimization fabrics are a geometric approach to real-time local motion generation, where motions are designed by the composition of several differential equations that exhibit a desired motion behavior. We generalize this framework to dynamic scenarios and nonholonomic robots and prove that fundamental properties can be conserved. We show...
journal article 2023
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