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FIGURE 17.8 The Ping))) ultrasonic sensor determines the distance to objects in the robot s path.
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17.2.5 RANGING SENSOR The infrared perimeter sensors detect objects that are close to the robot (hopefully before the bumpers are engaged) but they have a very limited range typically about 3 to 6 in. A robot often needs to be able to sense objects much further away. Ideally, the robot should be able to not only detect these objects, but determine how far away they are. One method for implementing such a sensor is with ultrasonic transducers. When the robot wants to check for a distant object (perhaps from 1 to 6 ft) it directs an ultrasonic wave (sound above the limits of human hearing) in the desired direction. If an object is present, the sound will be reflected back to the robot and detected. The amount of time it takes for the wave to reach the robot is directly proportional to the distance from the object. Parallax offers an ultrasonic sensor called the Ping))) as shown in Fig. 17.8. Parallax also offers a motorized turret that can rotate the sensor so the robot can look in different directions without actually rotating its body. The Ping))) sensor and its servocontrolled turret are shown mounted on the real-world robot in Fig. 17.11.
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17.2.6 THE COMPASS The simulated robot has a compass accurate to 1 . Parallax offers a low-cost electronic compass with an accuracy of about 6 . For many applications this is suf cient. Their documentation offers many ideas for dealing with sensor limitations. Figure 17.9 shows the compass module. Electronic compasses accurate to 1 or less are available from other companies, but at a higher cost.
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FIGURE 17.9
The compass module from Parallax is accurate to about 6 .
17.2.7 THE GPS The simulated robot has a global positioning system (GPS) capable of reporting the robot s location to within 1 screen pixel. Real-world GPS are often accurate to only 20 ft or so. Ways for improving on this accuracy and alternative approaches for determining a robot s location have been discussed in Chap. 15. Figure 17.10 shows a GPS module from Parallax. 17.2.8 THE CAMERA Digital cameras are an ideal way to give vision to a robot. In our simulation, the camera is limited to detecting colors in its eld of vision. This limitation makes sense for the simulation because there are no real objects of which to take pictures. Additionally, the discipline of robotic vision is a complicated eld of study that requires a book in its own right. To be able to analyze and make use of visual data, extensive mathematics and calculus is required. Parallax distributes a camera developed by the Seattle Robotics Club that can provide all of the functions needed for our robot and much more. The camera is shown mounted on our real-world robot in Fig. 17.11. Version 2.0.1 (and later) of RobotBASIC has support for serial and Bluetooth communication so that it is possible for a skilled hobbyist to download actual camera pictures
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FIGURE 17.10 The GPS module from Parallax is not nearly as accurate as the one in our simulated robot.
from a real-world robot to a RobotBASIC array. Advanced users can then use the mathematical and matrix capabilities of RobotBASIC to analyze and react to pictures in ways often only done at professional research and development laboratories. The skilled user could easily create a color image on RobotBASIC s terminal screen from the camera data, allowing for remote observation of the robot s environment. 17.2.9 BEACON DETECTION To our knowledge no one currently offers a beacon detection system for hobby robots. As you saw in Chap. 15, an appropriate beacon system can provide excellent navigational capabilities for a home or of ce based robot. Our simulated robot can detect a beacon mounted above other objects in the room, meaning that it can be seen even if there are objects on the oor between the robot and the beacon. The RobotBASIC simulation also provides the distance to the beacon if you wish to use it. In the simulation, the beacon is just an object of a speci ed color. Our realworld robot could actually use its camera to perform this function by looking for a speci c color. The vertical position of the color on the camera s image can be used to give an approximate distance to the beacon (the beacon color should appear higher on the image as the robot gets closer). There are many options for beacon detection. For example, instead of making the beacon a speci c color, it could be a visible light ashing at a xed frequency such as two pulses per second. The microcontroller could detect the beacon with the camera by comparing two pictures taken 1/4 second apart.
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