Multiresolutional Laser Radar

  • Rudolf Schwarte
Part of the NATO ASI Series book series (volume 63)


The INV-laser radar working group has spent considerable effort in the design and implementation of an advanced 3D-sensor, envisaging medium and large scale applications in robotics and automation, especially real—time measurements of shape, position, orientation and movement of three-dimensional objects as well as environment perception, path finding and docking of robotic vehicles. Using laser pulses instead of microwave pulses the operating principle is quite similar to that of a microwave radar. Realization of the projected laser radar, however, imposes a number of very crucial points.

This paper describes the main difficulties being encountered and presents elaborated solutions like an improved sensor head with so called mirror optics, a new fiber optic concept for ultimate precision, time windowing facilities for target selection, amplitude control, closed—loop real-time data processing for contour tracking and, finally, fast contour estimation procedures with special Kalman-jump—filter algorithms. The INV— laser radar is able to measure three coordinates, reflectivity and range rate of passive 3D—surface points at a primary measuring rate of some 10.000 Hz. After data processing the output data rate is reduced to some 100 Hz performing mm—resolution.

Experimental results of the INV-laser radar demonstrate an extraordinary precision, the ability to find and identify simple 3D-objects by measuring cross-sections and automatic 3D-edge resp. contour tracking as well as the process of taking a 3D—picture of a small workpiece by raster scanning. Since the latter mode consumes too much time it is more efficient first to analyze the 3D-scene by means of a 2D—vision system. Thereafter the laser radar is directed only to the interesting edges and structures in order to add the corresponding depth information.


Laser Radar Sensor Head Amplitude Control Raster Scanning Contour Tracking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • Rudolf Schwarte
    • 1
  1. 1.Institut für Nachriehtenverarbeitung (INV) Zentrum für Sensorsysteme (ZESS)University of SiegenSiegenW-Germany

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