| dc.description.abstract | The practice of robotics and machine vision involves the application of algorithms to
data. The data comes from sensors measuring the velocity of a wheel, the angle of a
robot arm’s joint or the intensities of millions of pixels that comprise an image of the
world that the robot is observing. For many robotic applications the amount of data
that needs to be processed, in real-time, is massive. For vision it can be of the order of
tens to hundreds of megabytes per second.
Progress in robots and machine vision has been, and continues to be, driven by
more effective ways to process data. This is achieved through new and more efficient
algorithms, and the dramatic increase in computational power that follows Moore’s
law. When I started in robotics and vision, in the mid 1980s, the IBM PC had been
recently released – it had a 4.77 MHz 16-bit microprocessor and 16 kbytes (expandable
to 256 k) of memory. Over the intervening 25 years computing power has doubled
16 times which is an increase by a factor of 65 000. In the late 1980s systems capable
of real-time image processing were large 19 inch racks of equipment such as shown
in Fig. 0.1. Today there is far more computing in just a small corner of a modern
microprocessor chip. | en_US |
