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Figure 4.27 Chapter 4
Color markers on the top of EPFL’s STeam Engine soccer robots enable a color-tracking sensor to
locate the robots and the ball in the soccer field.

control systems for mobile robots exclusively using optical flow have not yet proved to be
broadly effective.

4.1.8.4 Color-tracking sensors
Although depth from stereo will doubtless prove to be a popular application of vision-based
methods to mobile robotics, it mimics the functionality of existing sensors, including ultra-
sonic, laser, and optical rangefinders. An important aspect of vision-based sensing is that
the vision chip can provide sensing modalities and cues that no other mobile robot sensor
provides. One such novel sensing modality is detecting and tracking color in the environ-
ment.
Color represents an environmental characteristic that is orthogonal to range, and it rep-
resents both a natural cue and an artificial cue that can provide new information to a mobile
robot. For example, the annual robot soccer events make extensive use of color both for
environmental marking and for robot localization (see figure 4.27).
Color sensing has two important advantages. First, detection of color is a straightfor-
ward function of a single image, therefore no correspondence problem need be solved in
such algorithms. Second, because color sensing provides a new, independent environmen-
tal cue, if it is combined (i.e., sensor fusion) with existing cues, such as data from stereo
vision or laser rangefinding, we can expect significant information gains.
Efficient color-tracking sensors are now available commercially. Below, we briefly
describe two commercial, hardware-based color-tracking sensors, as well as a publicly
available software-based solution.