TR: neural robot hand-eye coordination

[Patrick van der Smagt]

The following technical report has been put in the connectionists
archive.

		Robot hand-eye coordination using neural networks

	P. Patrick van der Smagt, Frans C. A. Groen, and Ben J. A. Kr\"ose

			Department of Computer Systems
			University of Amsterdam
			TR CS--93--10

A self-learning, adaptive control system for a robot arm using a
vision system in a feedback loop is described both in simulation and
in practice.  The task of the control system is to position the
end-effector as accurately as possible directly above a target object,
so that it can be grasped.  The camera of the vision system is
positioned in the end-effector and visual information is used
to control the robot.   Knowledge of the size of the object is
used for obtaining 3D information from a single camera.  

The neural controller is shown to exhibit `real-time' learning 
behaviour, and adaptivity to unknown changes in the robot configuration.


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A postscript version of the paper can be obtained as follows:

  unix> ftp archive.cis.ohio-state.edu
  ftp> login name: anonymous
  ftp> password: xxx at yyy.zzz
  ftp> cd pub/neuroprose
  ftp> bin
  ftp> get smagt.hand-eye.ps.Z
  ftp> bye

The technical report is 23 pages long, about 2M.  Many Unix-systems
may require printing using
	lpr -s smagt.hand-eye.ps
to prevent the print spooler from overflowing.

The paper contains two bitmap photographs (on pages 4 and 9),
which may confuse some printers.  If you have trouble printing
the postscript file, remove those pictures as follows:

  unix> sed -e '/photographstart/,/photographend/d' < smagt.hand-eye.ps > mu.ps

(or remove the blocks which are enclosed between the lines
containing "photographstart" and "photographend" in the ps file
by hand) which will mutilate figures 1 and 6.  Then print mu.ps.

							Patrick