Page 137 - Introduction to Autonomous Mobile Robots

Chapter 4
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Camera output considerations. Although digital cameras have inherently digital output,
throughout the 1980s and early 1990s, most affordable vision modules provided analog
output signals, such as NTSC (National Television Standards Committee) and PAL (Phase
Alternating Line). These camera systems included a D/A converter which, ironically,
would be counteracted on the computer using a framegrabber, effectively an A/D converter
board situated, for example, on a computer’s bus. The D/A and A/D steps are far from
noisefree, and furthermore the color depth of the analog signal in such cameras was opti-
mized for human vision, not computer vision.
More recently, both CCD and CMOS technology vision systems provide digital signals
that can be directly utilized by the roboticist. At the most basic level, an imaging chip pro-
vides parallel digital I/O (input/output) pins that communicate discrete pixel level values.
Some vision modules make use of these direct digital signals, which must be handled sub-
ject to hard-time constraints governed by the imaging chip. To relieve the real-time
demands, researchers often place an image buffer chip between the imager’s digital output
and the computer’s digital inputs. Such chips, commonly used in webcams, capture a com-
plete image snapshot and enable non real time access to the pixels, usually in a single,
ordered pass.
At the highest level, a roboticist may choose instead to utilize a higher-level digital
transport protocol to communicate with an imager. Most common are the IEEE 1394
(Firewire) standard and the USB (and USB 2.0) standards, although some older imaging
modules also support serial (RS-232). To use any such high-level protocol, one must locate
or create driver code both for that communication layer and for the particular implementa-
tion details of the imaging chip. Take note, however, of the distinction between lossless
digital video and the standard digital video stream designed for human visual consumption.
Most digital video cameras provide digital output, but often only in compressed form. For
vision researchers, such compression must be avoided as it not only discards information
but even introduces image detail that does not actually exist, such as MPEG (Moving Pic-
ture Experts Group) discretization boundaries.

4.1.8.2 Visual ranging sensors
Range sensing is extremely important in mobile robotics as it is a basic input for successful
obstacle avoidance. As we have seen earlier in this chapter, a number of sensors are popular
in robotics explicitly for their ability to recover depth estimates: ultrasonic, laser
rangefinder, optical rangefinder, and so on. It is natural to attempt to implement ranging
functionality using vision chips as well.
However, a fundamental problem with visual images makes rangefinding relatively dif-
ficult. Any vision chip collapses the 3D world into a 2D image plane, thereby losing depth
information. If one can make strong assumptions regarding the size of objects in the world,
or their particular color and reflectance, then one can directly interpret the appearance of
the 2D image to recover depth. But such assumptions are rarely possible in real-world