We tested the GYROSTAR ENV-05S. This device is a sensor for angular velocity. Therefore the orientation must be calculated by integration of the angular velocity over time. The devices output is a voltage proportional to the angular velocity and relative to a reference. The test where done to find out under which conditions it is possible to use this device for estimation of orientation.
Principle of the Sensor
Inside the device is a triangle metal prism, which is fixed at two
points. The triangle prism is forced to vibrate by a piezoelectric ceramic ...
One of the problems of autonomous mobile systems is the continuous tracking of position and orientation. In most cases, this problem is solved by dead reckoning, based on measurement of wheel rotations or step counts and step width. Unfortunately dead reckoning leads to accumulation of drift errors and is very sensitive against slippery. In this paper an algorithm for tracking position and orientation is presented being nearly independent from odometry and its problems with slippery. To achieve this results, a rotating range-finder is used, delivering scans of the environmental structure. The properties of this structure are used to match the scans from different locations in order to find their translational and rotational displacement. For this purpose derivatives of range-finder scans are calculated which can be used to find position and orientation by crosscorrelation.
A Map Based On Laserscans Without Geometric Interpretation
A map for an autonomous mobile robot (AMR) in an indoor environment for the purpose of continuous position and orientation estimation is discussed. Unlike many other approaches, this map is not based on geometrical primitives like lines and polygons. An algorithm is shown, where the sensor data of a laser range finder can be used to establish this map without a geometrical interpretation of the data. This is done by converting single laser radar scans to statistical representations of the environment, so that a crosscorrelation of an actual converted scan and this representative results into the actual position and orientation in a global coordinate system. The map itself is build of representative scans for the positions where the AMR has been, so that it is able to find its position and orientation by comparing the actual scan with a scan stored in the map.
Exploration, Navigation and Self-Localization in an Autonomous Mobile Robot
In this paper the autonomous mobile vehicle MOBOT-IV is presented, which is capable of exploring an indoor-environment while building up an internal representation of its world. This internal model is used for the navigation of the vehicle during and after the exploration phase. In contrast to methods, which use a grid based or line based environment representation, in the approach presented in this paper, local sector maps are the basic data structure of the world model. This paper describes the method of the view-point-planning for map building, the use of this map for navigation and the method of external position estimation including the handling of an position error in a moving real-time system.