Searched for: contributor%3A%22Wisse%2C+Martijn+%28graduation+committee%29%22
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Sekoor Lakshmana Sankar, Prajish (author)
Wheeled-legged (hybrid) robots have the potential for highly agile and versatile locomotion in any real-world application requiring rapid, long-distance mobility skills on challenging terrain. The ability to walk and drive simultaneously is an attractive feature of these hybrid systems, but is unexplored in literature. This thesis work presents...
master thesis 2019
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van der Ploeg, Jorik (author)
A typical gait pattern of a healthy individual is characterized by coordinated kinematics of body segments that minimize the energy cost of transport. This is achieved by a well-coordinated sequence of energy generation, transmission, and absorption by muscles. Knowing the energy...
master thesis 2019
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van Duijneveldt, Joris (author)
The subject of this thesis is to investigate whether the Cerebellar Model Articulation Controller (CMAC) can be used to anticipate controller corrections and increase performance by reducing delays in humanoid robots. This question can be divided into two subquestions. Firstly, whether the CMAC is a suitable architecture for the prediction of...
master thesis 2019
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Bhoraskar, Akshay (author)
This study aims at a possible solution to predict the fuel consumption of heavy duty diesel trucks, particularly, the tractor semitrailer for their long haul operations using various machine learning techniques. It intends to provide a possible alternative to simulation or physics based models, which often are very complicated. The stringent...
master thesis 2019
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van den Broek, Maarten (author)
Bipedal running gaits may be self-stable if they rely on the intrinsic system dynamics to attenuate deviations. This use of passive dynamics for gait stability has been observed in biological running and applied for running robotics, supported with the results of numerical simulations. It is an important aspect of the development of fast and...
master thesis 2019
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Pezzato, Corrado (author)
Dealing with inherently unmodeled dynamics and large parameter variations or faults, is a challenging task while controlling robot manipulators. Classical control techniques cannot usually provide satisfactory responses, and often external supervision systems have to be designed to handle the faults. Recent research has shown that active...
master thesis 2019
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SHARMA, Sparsh (author)
The increasing complexity of mechanical systems has resulted in an increased usage and dependence on data driven modelling techniques in order to obtain simple yet accurate models of these systems. Neural networks have emerged as a popular modelling choice due to their proven ability to learn complex nonlinear relationships between inputs and...
master thesis 2019
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Bosma, Stijn (author)
A repetitive motion system supporting nano meter precision is positioned at high accelerations, which produces a force that disturbs the demanded accuracy requirements. Iterative learning control is used to learn optimal feedforward control signals for the attenuation this disturbance force. The iterative method comes with a limitation, as it...
master thesis 2019
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van Hofslot, Boris (author)
This research considers using center of mass (CoM) height variation as an input for balance control on a humanoid robot. Traditional balance strategies for humanoid robots are taking a step, control of the center of pressure (CoP) location, a result of the ‘ankle strategy’, and changing the angular momentum about the CoM, for example by a ‘hip...
master thesis 2019
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Hoogerwerf, Eert (author)
Human-robot collaboration can be improved if the motions of the robot are more legible and predictable. This can be achieved by making the motions more human-like. It is assumed that humans move optimal with respect to a certain objective or cost function. To find this function an inverse optimal control approach is developed. It uses a bilevel...
master thesis 2018
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Tsutsunava, Nick (author)
Kinodynamic planning is motion planning in state space and aims to satisfy kinematic and dynamic constraints. To reduce its computational cost, a popular approach is to use sampling based methods such as RRT with off-line machine learning for estimating the steering cost and inputs. However, scalability and robustness are still open challenges...
master thesis 2018
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van der Schaaf, J.B.J. (author)
Gait rehabilitation attempts to alleviate gait and balance impairments caused by spinal cord injury. Conventional gait rehabilitation often includes unloading a portion of the user’s weight with a vertical force. This vertical force enables people to practice stepping but makes forward propulsion more difficult. Users will adopt a compensatory...
master thesis 2018
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Voordouw, Janneke (author)
In this research the influence of the rower behavior and rigging setup on the boat performance is investigated in a data-driven model. There are different rowing styles and techniques between rowers. Making rowers row in synchrony, while important for the boat performance, is not easy. Rowers have their own signature rowing curve, of which only...
master thesis 2018
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Apte, Salil (author)
master thesis 2017
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Rastogi, Divyam (author)
Reinforcement Learning (RL) is a general purpose framework for designing controllers for non-linear systems. It tries to learn a controller (policy) by trial and error. This makes it highly suitable for systems which are difficult to control using conventional control methodologies, such as walking robots. Traditionally, RL has only been...
master thesis 2017
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de Geus, Marijke (author)
The focus of this project is two-fold: first it explores how animation can be used to make functional robots more intuitively understandable. A framework for functional robot developers, to apply animations in the designed behaviours of their products, is proposed. Second, it demonstrates the value of the incorporation of animated behaviours, as...
master thesis 2017
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