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Förslaget inkom 2006-04-15

Adaptive grid methods for on-line trajectory planning

OBS! ANSÖKNINGSTIDEN FÖR DETTA EXJOBB HAR LÖPT UT.
A key part of the autonomy of an unmanned aerial vehicle (UAV) is the path planning problem, where a tentatively optimal path is laid out for the vehicle autopilot to follow. Traditionally, trajectory optimization problems are solved with classical methods from optimal control, which means that the planning problem in general has to be solved off-line, due to the computational complexity. In modern day scenarios however, where the available information is incomplete, unreliable and changeable, this is no longer a feasible solution.

Since Mars 2005, the Division of Optimization and Systems Theory at KTH,
cooperatively conducts research within this field together with the
Department of Autonomous Systems at the Swedish Defence Research Agency
(FOI). The central topic of the project is the problem of obtaining
methods and computationally efficient algorithms for path
planning/re-planning, that are possible to implement in real-time.

The work so far has indicated the spatial decomposition of the environment as a promising area for speeding up the path planning process considerably. The proposed master's thesis project has two objectives; Firstly, the candidate should survey and map out the existing work on adaptive grid generation and multi-resolution representation of a 3D environment. Then, based on this, he/she is expected to outline a computationally efficient grid generation algorithm, tailored for the particular problems considered.

The nature of the proposed project, calls for a candidate characterized by strong abstraction capabilities, a good general mathematical understanding and effective written and oral communications skills. As parts of the project will require the extension of existing software, programming skills are advisable.

To submit your application, please send an email, including your resume, academic records and a short description of your main interests to [email protected]

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