Page 35 - Rapid Learning in Robotics

2.4 Remote Sensing: Vision 21

These initial results from the new tactile sensor system are very promis-
ing. We expect to (i) fill the present gap in proprioceptive sensory infor-
mation on the oil cylinder friction state and therefore better finger fine
control; (ii) get fast contact state information for task-oriented low-level
grasp reflexes; (iii) obtain reliable contact state information for signaling
higher-level semi-autonomous robot motion controllers.

2.4 Remote Sensing: Vision

In contrast to the processing of force-torque values, the information gained
by the image processing system is of very high-dimensional nature. The
computational demands are enormous and require special effort to quickly
reduce the huge amount of raw pixel values to useful task-specific infor-
mation.
Our vision related hardware currently offers a variety of CCD cameras
(color and monochrome), frame grabbers and two specialized image pro-
cessors systems, which allow rapid pre-processing. The main subsystems
are (i) two Androx ICS-400 boards in the VME bus system of “druide”(see
Fig. 2.2), and (ii) A MaxVideo-200 with a DigiColor frame grabber exten-
sion from Datacube Inc.
Each system allows simultaneous frame grabbing of several video chan-
nels (Androx: 4, Datacube: 3-of-6 + 1-of-4), image storage, image oper-
ations, and display of results on a RGB monitor. Image operations are
called by library functions on the Sun hosts, which are then scheduled for
the parallel processors. The architecture differs: each Androx system uses
four DSP operating on shared memory, while the Datacube system uses a
collection of special pipeline processors working easily in frame rate (max
20 MByte/s). All these processors and crossbar switches are register pro-
grammable via the VME bus. Fortunately there are several layers of library
calls, helping to organize the pipelines and their timely switching (by pipe
altering threads).
Specially the latter machine exhibits high performance if it is well adapted
to the task. The price for the speed is the sophistication and the complexity
of the parallel machines and the substantial lack of debugging information
provided in the large, parallel, and fast switching data streams. This lack
of debug tools makes code development somehow tedious.