Abstract
Many buildings are already equipped with a WLAN infrastructure, as an inexpensive communication technology. In this paper two methods that estimate the position and the heading (pose) of a mobile robot using WLAN technology are described. The proposed techniques for localizing a mobile robot are based on the use of received signal strength values of WLAN access points in range. Both use a radio map based method. For interpolation of the radio map weigthed Euclidean distance and Euclidean distance in combination with Delaunay triangulation is proposed. Measured signal strength values of an omnidirectional antenna and a beam antenna are compared with the values of a radio map, in order to estimate the pose of a mobile robot, whereby the directionality of the beam antenna is used to estimate the heading of the robot. The paper presents the experimental results of measurements in an office building.
Highlights
Navigation is a key ability of mobile robots
Measured signal strength values of an omnidirectional antenna and a beam antenna are compared with the values of a radio map, in order to estimate the pose of a mobile robot, whereby the directionality of the beam antenna is used to estimate the heading of the robot
The wireless extension (WE) provide an interface via ioctl(), which is documented in wireless.h
Summary
Navigation is a key ability of mobile robots. The task of navigation can be divided into localization and path planning. Aim of localization is to estimate the pose (position and heading) of a mobile robot with respect to its environment. There are three different kinds of localization problems in mobile robotics: position tracking, global localization and kidnapped robot problem. The problem is called global localization, if there is no priori estimate of the pose. The kidnapped robot problem describes a situation, where a localized robot is moved to a different place without its knowledge. It is often used to test a robot's ability to recover from localization failures. Approaches which are capable of solving the global localization problem can be modified such that they can solve the kidnapped robot problem [1]
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