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Copyright 2006, 2001, 1987 by The McGraw-Hill Companies, Inc. Click here for terms of use.
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OBJECT DETECTION
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30.1 Design Overview
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Object detection can be further divided into collision avoidance and collision detection. With collision avoidance, the robot uses noncontact techniques to determine the proximity of objects around it. It then avoids any objects it detects. Collision detection concerns what happens when the robot has already gone too far, and contact has been made with whatever foreign object was unlucky enough to be in the machine s path. Collision avoidance can be further broken down into two subtypes: near-object detection and far-object detection. By its nature, all cases of collision detection involve making contact with nearby objects. All of these concepts are discussed in this chapter. Additionally, robot builders commonly use certain object detection methods to navigate a robot from one spot to the next. Many of these techniques are introduced here because they are relevant to object detection, but we develop them more fully in 33, Navigation.
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30.1.1 NEAR-OBJECT DETECTION
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Near-object detection does just what its name implies: it senses objects that are close by, from perhaps just a breath away to as much as 8 or 10 ft. These are objects that a robot can consider to be in its immediate environment objects it may have to deal with, and soon. These objects may be people, animals, furniture, or other robots. By detecting them, your robot can take appropriate action, which is defined by the program you give it. Your robot may be programmed to come up to people and ask them their name. Or it might be programmed to run away whenever it sees movement. In either case, it won t be able to accomplish either behavior unless it can detect objects in its immediate area. There are two ways to effect near-object detection: proximity and distance:
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Proximity sensors care only that some object is within a zone of relevance. That is, if an object is near enough in the physical scene the robot is looking at, the sensor detects it and triggers the appropriate circuit in the robot. Objects beyond the proximal range of a sensor are effectively ignored because they cannot be detected. Distance measurement sensors determine the distance between the sensor and to some object within range. Distance measurement techniques vary; almost all have notable minimum and maximum ranges. Few yield accurate data if an object is very close to the robot. Likewise, objects just outside the sensor s effective range can yield inaccurate results. Large objects far away may appear closer than they really are; very close small objects may appear abnormally larger than they really are, and so on. If there are multiple objects within the sensor s field of view, the robot may have difficulty sorting them out and figuring out which one is closest (and is the most likely danger).
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Sensors have depth and breadth limitations: depth is the maximum distance an object can be from the robot and still be detected by the sensor. Breadth is the maximum height and width of the sensor detection area. Some sensors see in a relatively narrow zone, typ-
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30.1 DESIGN OVERVIEW
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ically in a conical pattern, like the beam of a flashlight. Light sensors are a good example. Adding a lens in front of the sensor narrows the pattern even more. Other sensors have specific breadth patterns. The typical passive infrared sensor (the kind used on motion alarms) uses a Fresnel lens that expands the field of coverage on the top but collapses it on the bottom. This makes the sensor better suited for detecting human motion instead of cats, dogs, and other furry creatures (humans being, on average, taller than furry creatures). The detector uses a pyroelectric element to sense changes in heat patterns in front of it.
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