Page 136 - Introduction to Autonomous Mobile Robots

Perception

Figure 4.18 121
A commercially available, low-cost CMOS camera with lens attached.

approach: the pixel-specific circuitry next to every pixel measures and amplifies the pixel’s
signal, all in parallel for every pixel in the array. Using more traditional traces from general
semiconductor chips, the resulting pixel values are all carried to their destinations.
CMOS has a number of advantages over CCD technologies. First and foremost, there is
no need for the specialized clock drivers and circuitry required in the CCD to transfer each
pixel’s charge down all of the array columns and across all of its rows. This also means that
specialized semiconductor manufacturing processes are not required to create CMOS
chips. Therefore, the same production lines that create microchips can create inexpensive
CMOS chips as well (see figure 4.18). The CMOS chip is so much simpler that it consumes
significantly less power; incredibly, it operates with a power consumption that is one-hun-
dredth the power consumption of a CCD chip. In a mobile robot, power is a scarce resource
and therefore this is an important advantage.
On the other hand, the CMOS chip also faces several disadvantages. Most importantly,
the circuitry next to each pixel consumes valuable real estate on the face of the light-detect-
ing array. Many photons hit the transistors rather than the photodiode, making the CMOS
chip significantly less sensitive than an equivalent CCD chip. Second, the CMOS technol-
ogy is younger and, as a result, the best resolution that one can purchase in CMOS format
continues to be far inferior to the best CCD chips available. Time will doubtless bring the
high-end CMOS imagers closer to CCD imaging performance.
Given this summary of the mechanism behind CCD and CMOS chips, one can appreci-
ate the sensitivity of any vision-based robot sensor to its environment. As compared to the
human eye, these chips all have far poorer adaptation, cross-sensitivity, and dynamic range.
As a result, vision sensors today continue to be fragile. Only over time, as the underlying
performance of imaging chips improves, will significantly more robust vision-based sen-
sors for mobile robots be available.