Abstract
A current project at the Institute of Robotics, Swiss Federal Institute of Technology is working towards the goal of distributing internal mail in a new office building. As a part of this effort we have investigated new methods in navigation and localisation of mobile robots. The preliminary results hereof are presented in this paper.
A mobile robot experimental platform suited for an office environment has been constructed. A picture of the platform can be seen in figure 1. This robot, intended for research into sensing and control for distribution applications, is equipped with a high performance embedded processor and a variety of sensors. One of the most important sensors is a scanned laser range finder. The performance of this sensor is discussed later in this paper, as are algorithms that exploit this sensor data for localisation and local navigation. Several algorithms for local navigation have been implemented on the robot, this paper will discuss one of these based on a new neural network architecture. Finally test-results from applying these algorithm on the real robot platform (using the embedded computer) and real sensor data are presented.
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Vestli, S.J., Tschichold-Gürman, N., Andersson, H. (1994). Learning control and localisation of mobile robots. In: Levi, P., Bräunl, T. (eds) Autonome Mobile Systeme 1994. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79267-0_19
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DOI: https://doi.org/10.1007/978-3-642-79267-0_19
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