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identification system The robot examines unknown rocks based on known characteristics of rocks, such as color, hardness, scratchability, acid reaction tests, mass, etc The expert system fails if it inadvertently picks up a piece of ice that melts to water during the tests Well, it fails as long as the designer(s) never anticipated the robot picking up a piece of ice by mistake and made allowances for it Neural (behavior based) systems are not programmed and are more adap tive, as shown in the previous example But is a neural system suitable for this task of rock identification Probably not! There are instances in which expert systems are the method of choice One shouldn t blindly assume one system is better than the other in all cases To date, behavior based robots are more successful at task accomplishments such as traveling over unfamiliar and rough terrain than are programmed robots (Other neural based intelligence includes speech recognition, artificial vision, speech generation, complex analysis of stock market data, and life insurance policies) Where s the Intelligence Behavior based systems at their most basic level are neural reflex actions, so where s the intelligence in that However, true behavior based systems, when layered on top of one another, generate what appears to be (meaning to us homo sapiens) intelligence actions This is not a consciousness mind, which is a whole other category of intelligence, but the layer behavior based circuits mimic intelligent actions quite convincingly Layered Behavioral Responses Let s layer a few behavioral responses on top of one another to see how intel ligence behavior emerges This particular robot is a modified photovore It will use a number of standard photoresistors as sensors Layer 1 is a simple on and off system It uses a single photoresistor to read ambient light intensity In darkness the system turns itself off and shuts down all electric power to the robot When the ambient light increases to a low threshold, the system turns itself on and the robot travels forward slowly Layer 2 is a two photoresistor sensor It determines in which direction the light intensity is greater These sensors steer the robot in the direction of the greatest light intensity Layer 3 is a single photoresistor sensor Under high intensity light it shuts down the robot s drive system and allows the robot to bathe in strong intensi ty light An outsider who didn t know how this robot was wired would observe the fol lowing behavior At night the robot sleeps At dawn it begins to travel, looking for a bright light source (food) When it finds a sufficiently bright light source, it stops to feed, recharging its batteries through solar panels.

where C = hourly capacity of the runway-use configuration in operations per hour Cb = ideal or base capacity of the runway-use configuration E = exit adjustment factor for the number and location of runway exits T = touch-and-go adjustment factor The use of this equation and the charts are illustrated by Example Problem 12-7

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CWDM pluggable transceivers that work with transmission rates of 100 Mbps to 27 Gbps are available with optical budgets of 25 dB Maximum link loss for both 8-channel and 16-channel CWDM designs are within optical budget for wavelengths 1471 to 1611 nm, 8-channel systems The 16-channel CWDM can be considered for use to obtain two or four more channels not in the water peak, 1331, 1311, 1291, and 1271 nm Measuring losses at these wavelengths results in a maximum loss of 140 dB Using Eq (613) we obtain maximum link loss at these wavelengths as follows: 2 5 0 + 14 0 = 24 0dB This is within the pluggable transceiver s optical budget of 25 dB Therefore, as long as the high attenuation channels are avoided, a 16-channel CWDM can be used to achieve twelve usable channels Since cable fiber type is unknown, chromatic dispersion measurements were conducted across the usable CWDM band, which resulted in minimum CD of 0 ps/nm and maximum CD of 300 ps/nm Equipment specifications CD limit is 500 ps/nm Therefore, CD is not a concern for this deployment

Example Problem 12-7 It is required to find the VFR and IFR hourly capacity of the runway system shown in Fig 12-12 The runway-use strategy is as shown In VFR weather, the traffic consists of 3 single-engine, 20 light twin-engine, 25 large transport-type, and 2 wide-bodied aircraft Arrivals constitute 40 percent of the operations and there are approximately three touch and-go operations

It is possible to cascade a DWDM multiplexer with a CWDM multiplexer system to increase link capacity, see Fig 616 CWDM channel passband of 65 nm can pass up to sixteen 100 GHz channels and eight 200 GHz channels, see Table C5 in App C CWDM channel 1531 nm has a passband of 152462 to 153738 nm, CWDM channel 1551 nm has a passband of 154462 to 155738 nm, CWDM channel 1571 nm has a passband of 156462 to 157738 nm (assuming laser drift of 012 nm) These passbands fall within the DWDM S, C, and L bands, see Fig 610, where DWDM lasers (SFP, Xenpaks, etc) are available However, two concerns need to be addressed for such a configuration to be practical

FIGURE 12-12

So our simple photovore robot exhibits three (dare we say intelligent ) behaviors sleep, searching or hunting, and feeding That s not bad for a hand ful of components and some neural glue Behavior Based Robotics Behavior based programs and robotics are not new concepts Seminal work has been written and experiments carried out since the 1940s In the 1940s neural networks and behavior based robotics were hardwired electrical com ponents In the 1940s Dr W Grey Walter built two turtlelike mobile robots that exhib it complex behavior using a few electrical neurons The behavior generated was at the time called robotic reflexes Today this behavior is more accurately described as layered neural architecture In the 1980s Valentino Braitenberg wrote a book entitled Vehicles Experiments in Synthetic Psychology in which he described complex behavior emerging from the use of a few artificial neurons Rodney Brooks, head of MIT s Artificial Intelligence Laboratory, is a leader in the field of subsumption architecture, which again is behavior based and neural Mark Tilden, creator of the nervous network technology, which again is reflex based, doesn t program strategies such as walking into his biomorphic robots Instead he creates a nervous network whose desired state creates a walking gait What these scientists have discovered is that neural behavior based archi tecture offers unique advantages over standard based expert programming In this book we will build a few behavior based robots, using the PIC micro controller extensively in their construction

Runway layout for Example Problem 12-7

1310 1551

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