Chapter 13 – Knowing Where You Are

Publisher Summary This chapter introduces the concepts of navigation; describes how positioning methods can be categorized into two general classes: absolute and relative positioning, the first based on external reference points, and the latter on internal measurements. Then it provides some examples for both the categories, showing solutions, and tricks that suit the possibilities of the MINDSTORMS system. In discussing absolute positioning, it introduces navigation on pads equipped with grids or gradients, and to the use of laser beams to locate a robot in a room. As for relative positioning, this chapter also explains how to equip the robot for proper measurements, with math to convert those measurements into coordinates. Absolute positioning refers to the robot using some external reference point to figure out its own position. These can be landmarks in the environment, either natural landmarks recognized through some kind of artificial vision or more often, artificial landmarks easily identified by robot. Another common approach includes using radio (or light) beacons as landmarks, like the systems used by planes and ships to find the route under any weather condition. Absolute positioning requires a lot of effort. Relative positioning, on the other hand, doesn't require the robot to know anything about the environment. It deduces its position from its previous position and the movements it made since the last known position. This is usually achieved through the use of encoders that precisely monitor the turns of the wheels, but there are also inertial systems that measure changes in speed and direction. This method is also called dead reckoning.