Abstract. Image processing for autonomous robots is nowadays very popular. In our paper, we show a method how to extract information from a camera attached on a robot to acquire locations of targets the robot is looking for. We apply maximally stable colour regions (a method originally used for image matching) to obtain an initial set of candidate regions. This set is then filtered using application specific filters to find only the regions that correspond to scene elements of interest. The presented method has been applied in practice and performs well even under varying illumination conditions since it does not rely heavily on manually specified colour thresholds. Furthermore, no colour calibration is needed.
The original versions of the Chapters 17 and 25 were previously published as non-open access. They have now been changed to open access under the CC BY 4.0 license and the copyright holder updated to ‘The Author(s)’. The book and the chapters have been updated with the changes.
Robot competitions are more and more used as a tool for education as well as an entertainment activity. This workshop brings together organizers, participants, teachers, and other people interested to share best practices, discuss issues and possibly improve their work.
In recent years, many so called "robotic toys" appeared at the market. Though these devices are called toys and they are primarily intended for games, they provide a set of sensors and actuators that can be controlled from a computer. Hence these robotic devices may serve as non-expensive research tools, in particular for developing advanced software for controlling them. This paper describes a controller for landing of an AR.Drone, a quadricopter marketed by Parrot Inc. This controller is designed for fully autonomous landing to a given visual pattern and for hovering above the pattern. We will show how to collect input information for the controller and how to use it in a classical PID controller.
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