Erik-Jan van Kampen

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Bio-inspired methods can provide efficient solutions to perform autonomous landing for Micro Air Vehicles (MAVs). Flying insects such as honeybees perform vertical landings by keeping flow divergence constant. This leads to an exponential decay of both height and vertical velocity, and allows for smooth and safe landings. However, the presence of noise and(More)
In science and engineering there often is a need for the approximation of scattered multi-dimensional data. A class of powerful scattered data approximators are the multivariate simplex B-splines. Multivariate simplex B-splines consist of Bernstein basis polynomials that are defined on a geometrical structure called a triangulation. Multivariate simplex(More)
The fractions of the left and the right coronary arterial flow determining coronary sinus flow (f acs,f acd) were measured in the open-chest dog. Both coronary arteries were isolated and perfused at the same pressure, while the sinus outflow was isolated and drained against the prevailing mean pressure in the right atrium. The fractions were determined by(More)
Goal-finding in an unknown maze is a challenging problem for a Reinforcement Learning agent, because the corresponding state space can be large if not intractable, and the agent does not usually have a model of the environment. Hierarchical Reinforcement Learning has been shown in the past to improve tractability and learning time of complex problems, as(More)
This paper proposes a taxonomy of conflict detection and resolution (CD&R) approaches for operating unmanned aerial vehicles (UAVs) in an integrated airspace. Possible approaches for UAVs are surveyed and broken down based on their types of surveillance, coordination, maneuvering, and autonomy. The factors are combined back selectively, with regard(More)
The design of unknown-input decoupled observers and filters requires the assumption of an existence condition in the literature. This paper addresses an unknown input filtering problem where the existence condition is not satisfied. Instead of designing a traditional unknown input decoupled filter, a Double-Model Adaptive Estimation approach is extended to(More)
Navigation in an unknown or uncertain environment is a challenging task for an autonomous agent. The agent is expected to behave independently and to learn the suitable action to take for a given situation. Reinforcement Learning could be used to help the agent adapt to an unknown environment and learn the right actions to take. This paper presents the(More)