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8.3.4 Robot Visual Sensing Tasks
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Robots will work in unpleasant locations. Health hazards are of no concern to them. Special safety equipment is not required for a robot spraying paint, welding, or handling radioactive materials or chemicals. All this adds up to reduced production costs. As the day progresses, the tired worker has a tendency to pay less attention to details, and the quality of the finished product may suffer. This is especially noticeable in automobiles where spray paint can run or sag and weld joints may not be made perfectly. The panels of the car may not be aligned, and the finished product may not operate properly, with predictable customer dissatisfaction. In pharmaceutical production, too, an operator inspecting and verifying lot number and expiration date may become fatigued and fail to inspect for sensitive information. Robots, on the other hand, do not tire or change their work habits unless they are programmed to do so. They maintain the same level of operation throughout the day. With vision-sensing systems and robots, it is possible for American manufacturers to compete against lower labor costs in foreign countries. The initial investment is the only problem. After such an investment, the overall operation costs of the production line are reduced or held constant. Small educational robots can be used to retrain humans to operate and maintain robots. The roles of robots with machine vision can be summarized as follows: Handling and assembly. Recognizing position/orientation of objects to be handled or assembled, determining presence or absence of parts, and detecting parts not meeting required specifications Part classification. Identifying objects and recognizing characters Inspection. Checking for assembly and processing, surface defects, and dimensions Fabrications. Making investment castings, grinding, deburring, water-jet cutting, assembling wire harnesses, gluing, sealing, puttying, drilling, fitting, and routing Welding. automobiles, furniture, and steel structures automobiles, furniture, and other objects Spray painting.
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Robots Utilizing Vision Systems to Recognize Objects
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A basic use of vision is recognizing familiar objects. It is easy to see that this ability should be an important one for robot vision. It can be a task in itself, as in counting the number of each kind of bolt in a mixed lot on a conveyer belt. It can also be an adjunct to other tasks for example, recognizing a particular object before trying to locate it precisely, or before inspecting it for defects.
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FIGURE 8.3 Recognition of a learned object.
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It is important to note that this task actually has two distinct parts: first, object familiarization that is, learning what an object looks like, then object recognition (Fig. 8.3). There are many ways of learning to recognize objects. Humans can learn from verbal descriptions of the objects, or they can be shown one or more typical items. A brief description of a pencil is enough to help someone identify many unfamiliar items as pencil. Shown a few pencils, humans can recognize different types of pencils, whether they look exactly like the samples or not. Robot-vision systems are not so powerful, but both these approaches to training still apply to them. Robots can be given descriptions of what they are to recognize, perhaps derived from CAD data to guide a machine tool (Fig. 8.4) or they can be shown samples, then be expected to recognize objects more or less like the samples. Recognizing objects once they have been learned is the second, and more difficult, part of the task. Several basic questions arise in virtually every recognition task. Among them are What are the choices and What can change Specifying the actual task completely is normally the hardest part of the application. When this has been accomplished, the basic question is, for what particular vision features should the search begin to
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