Gathering information, especially about the immediately surrounding world, is a central aspect of any smart device, whether it is a robot, a partially autonomous vehicle, or a mobile handheld device. This talk addresses stochastic methods for filtering sensor data, which is gathered by mobile devices, to model the devices' location and eventually also relevant parts of their dynamic environment. This is done with a focus on online algorithms and computation on these mobile devices themselves, which implies limited available processing power and the necessity for computational efficiency. Different application scenarios, namely humanoid robot soccer and indoor smartphone localization, provide examples to impart a better understanding about the conception and design of stochastic filtering solutions and to show localization algorithms beyond the current state of the art.
Universität Bonn, Institute for Computer Science, Departments: I, II, III, IV, V, VI