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There are subtle things about an image that a machine will not notice unless it has advanced AI. How, for example, is a robot to know whether an object presents a threat Is that four-legged thing there a big dog, or is it a bear cub How is a robot to forecast the behavior of an object Is that stationary biped a human or a mannequin Why is it holding a stick Is the stick a weapon What does the biped want to do with the stick, if anything The biped could be a department-store dummy with a closedup umbrella or a baseball bat. It could be an old man with a cane. Maybe it is a hunter with a rifle. You can think up various images that look similar, but that have completely different meanings. You know right away if a person is carrying a tire iron to help you fix a flat tire, or if the person is clutching it with the intention of smashing something up. How is

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Limitations The technology for telepresence has existed for some time. But certain logistical problems have always bedeviled engineers committed to developing such systems. The most serious limitation is the fact that telemetry cannot, and never will, travel faster than the speed of light in free space. This is not a problem over short-range links (a few hundred kilome-

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Robotic hearing and vision 655 a robot to determine subtle things like this from the images it sees It is important for a police robot or a security robot to know what constitutes a threat and what does not. In some robot applications, it isn t necessary for the robot to know much about what s happening. Simple object recognition is good enough. Industrial robots are programmed to look for certain things, and usually they aren t hard to identify. A bottle that is too tall or too short, a surface that s out of alignment, or a flaw in a piece of fabric is easy to pick out.

Sensitivity is the ability of a machine to see in dim light or to detect weak impulses at invisible wavelengths. In some environments, high sensitivity is necessary. In others, it is not needed and might not be wanted. A robot that works in bright sunlight doesn t need to be able to see well in a dark cave. A robot designed for working in mines, pipes, or caverns must be able to see in dim light, using a system that might be blinded by ordinary daylight. Resolution is the extent to which a machine can differentiate between objects. The better the resolution, the keener the vision. Human eyes have excellent resolution, but machines can be designed with greater resolution. In general, the better the resolution, the more confined the field of vision must be. To understand why this is true, think of a telescope. The higher the magnification, the better the resolution (up to a certain maximum useful magnification). Increasing the magnification reduces the angle, or field, of vision. Zeroing in on one object or zone is done at the expense of other objects or zones. Sensitivity and resolution are interdependent. If all other factors remain constant, improved sensitivity causes a sacrifice in resolution. Also, the better the resolution, the less well the vision system will function in dim light.

ters or less), but it is slow in outer space, and nigh impractical in interplanetary operations. The moon is approximately 1.3 light-seconds away from the earth; that means that any command sent to a telechir from the earth to the moon takes 1.3 s to get there, and any data from the telechir takes another 1.3 s to get back. For planets in the solar system, the delay is on the order of several minutes to several hours. On an interstellar scale, telepresence is out of the question. The nearest stars are at distances of several light-years. Another problem is the resolution of the robot s vision. A human being with good eyesight can see things in considerable detail. To send images in real-life detail, at reasonable speed, requires a signal with broad bandwidth. There are engineering problems (and cost problems) that go along with this. However, if one is willing to deal with the cost and accommodate the signal bandwidth, robot vision systems can be designed that offer optical resolution superior to human eyesight. Still another limitation is best put as a question: How will a robot be able to feel something and transmit these impulses to the human brain For example, an apple feels smooth, a peach feels fuzzy, and an orange feels shiny yet bumpy. How can this sense of texture be realistically transmitted to the human brain

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