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The opposite of serial behavior would be parallel behavior. But you can t really have a bunch of behaviors active all at the same time, at least not if they are driving the same robot. What you need is a way to layer these behaviors, activating the right one at the right time. If you ve been keeping up, you will notice right away that the big challenge is knowing when the right time is to activate a behavior. It could be when
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Fig. 17-6.
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Subsumption layering.
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the battery is low, or when the robot has bumped into a wall, or when a command is given to the robot. Maybe the robot needs to seek out some person and deliver a message. Some of these conditions are easy to detect, others are harder. Assuming that each behavior is able to determine for itself when it should be active, these behaviors could be layered. Figure 17-6 shows three possible navigation behaviors for a mobile robotic explorer. When there is nothing else happening, the robot is free to explore randomly. If it has been directed to go somewhere specific, the path planner takes control from the explore module. The robot then travels to the destination. If, once it gets there, the path planner releases control, the robot starts to explore again. If the robot finds itself in trouble, the emergency avoidance module takes over until the robot is in the clear again. The different behaviors override, or subsume, each other, making this a subsumption architecture. This approach to merging multiple simple behaviors into a cooperating, complex whole was invented by Rodney Brooks, who is currently the director of the MIT Computer Science and Artificial Intelligence Laboratory. The complete subsumption system allows behavior modules to override inputs as well as outputs, and to reset other modules. Extensions to the basic system provide global information, representing hormones and other systemic indicators, to help control the overall behavior. Most modules in a subsumption system are reactive behaviors. These are like reflexes, though a bit more complex than the reflexive PID controller shown above. A reactive behavior doesn t do any planning, but reacts to its sensory input. Layers of reactive behavior provide an excellent middle layer in robotic control, giving the robot complex behaviors from small, easily programmed pieces. These, in turn, give the robot the ability to react smoothly and quickly to its environment.
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CHAPTER 17 Intelligent Behavior
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While mindlessly roaming around an environment is good for theoretical robots and, perhaps, vacuum cleaners and mine-clearing robots, other applications require a more structured approach. Something that provides the Goal from Fig. 17-6. It may seem like the best way to provide high-level control for your robot is to just write code to do what you want. This is a heuristic approach. A heuristic is a solution to a problem that solves the problem, but doesn t guarantee that the solution is the best one. It just gets the job done. In the long run, an undisciplined approach causes more problems than it solves. If the system is going to have a long life it pays to put more effort into the control system.
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SCRIPTING
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As mentioned above, many robots don t need intelligence, they just need some coherent guidance. In this case, a scripting language works perfectly well to control their actions. GM control codes, mentioned in 16, are a form of scripting language. For fancier robots, like robot arms, the control gets more complicated. A script would have to specify three-dimensional position in space, plus information about the angle of the end actuator. This is six axes of information, X, Y, Z, and pitch, roll, and yaw (angles around the axes). If there are obstacles to avoid, that adds to the complexity. Once you have decided on a position and rotation in space, the lower-level controller has to calculate the exact angles all of the joints must take to reach that position. This is the process of inverse kinematics and requires some heavy-duty mathematics.
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