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A PID or other reflexive control is fine for the most low-level tasks. There are times, however, when you want your machine to perform a series of actions, one after the other. Industrial robots don t need intelligence, per se, but do need to have predictable behavior. These robots will consist of some low-level reflexes and a bunch of simple commands to execute, one after another. For another example, in a competition you need to might need to follow a path for a certain distance, retrieve an object, and then return to the start. A Mars explorer may be given a set of tasks by the ground control and it must then carry them out, one at a time, until it is done. A smart Mars explorer would even be able to skip a task if it found itself unable to complete it. There is not much to say on the topic of serial behaviors, though there are some subtleties to be aware of when implementing them. The first is, how does the robot know when to stop one behavior and start the next behavior You could do something simple like drive forwards for 10 seconds or turn this wheel 100 times, but those are special cases that are only useful in a controlled environment. If you are a Mars explorer, how do you know when you are next to that funny-looking rock If you are driving over rough or slippery ground, how do you know when you have gone 100 feet Some of these questions might
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CHAPTER 17 Intelligent Behavior
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be answered by specialized sub-programs that can recognize such a poorly defined situation. This is difficult, one of those hard to define tasks like recognizing faces. Animals do it all the time, robots have to work really hard on the problem. Even when you have a situation where it is easy to tell when to switch tasks, such as when you have crossed a black line on the ground, you have bumped into a wall, or perhaps wandered into a shadow, you still don t know exactly where you are. You may have crossed a line, but at what angle How far did you roll over it before you came to a stop If the next step in the task relies on the robot being in a particular position or situated next to something just right, you will probably need a bit of code to align the robot before it really transitions. Everything a robot, or any other machine, does has error in it. Some errors are well behaved, like the backlash of gears. The error stays within a known range and doesn t grow over time. Other kinds of error get worse over time. If you have a slipping drive belt between a motor and actuator on your robot, that slippage will make the error in position grow worse over time. Mobile robots have this problem no matter how they are built. The interface between their wheels (or treads, or legs, or whatever) and the ground is not mathematically perfect. Any calculations used to determine the robot s position based on what the wheels have done are going to have errors. Every time the robot turns or moves, a little more error creeps into the picture. More feedback can be used to reduce the error. Distance sensors, cameras, bump switches, GPS, anything that can interact with the outside world, can provide a second opinion on the robot s position. When you have more than one way of estimating the robot s position, you can combine the results to reduce the error of any one technique. This sensor fusion is not easy, but at least it is possible.
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