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After completion of the module students are able to - understand cooperative positioning principles - understand and apply estimation theory methods for the analysis of swarm navigation performance - design a swarm navigation system based on radio ranging - transfer the learned knowledge to a wide range of applications and environments, which range from indoors, underwater to extraterrestrial exploration.

- Introduction, challenges and objectives - Review of Estimation theory - Inference of position information from radio signals - Design of ranging signals for a robotic swarm - Cooperative radio based localization - Robot constellations for high accuracy mapping and positioning - Robot control for constellation optimization and goal approaching - Simulation/Programming excercises

A strong mathematical background is expected, especially in signal processing, probability theory and analysis.

During the lectures students are instructed in a teacher-centered style. In addition to the individual learning, the students are encouraged to exchange knowledge with their colleagues in solving homework problems. Solutions are discussed in tutorials.

In an oral exam of 30 minutes students will be asked to design components of a navigation system for a swarm of robots, e.g. by recalling an appropriate signal model, identifying and applying Bayesian methods for range and position estimation, applying estimation theory methods for performance valuation and optimization.

- "Statistical Signal Processing - Estimation Theory"; Steven M. Kay; Prentice Hall Signal Processing Series; ISBN:0-13-345711-7; - "Detection and Estimation: Theory and its Applications"; Thomas Schonhoff and Arthur A.Giordano; Prentice Hall, 1st Edition, 2006; ISBN 0-1308-9499-0; - "Digital Communications"; John G. Proakis; McGraw-Hill, 3rd Edition, 1995; ISBN 0-07-051726-6;