Team Members:_______________________________________________________________________________

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Robot Name_____________________________________ Robot Gender (Male/Female or Undecided)__________

Instructor Initials	Robot Project
	Task 1 - Build a robot. Use fehmbot as your model. Remember the body of the robot has to be strong enough and big enough to support the battery pack and the handy board. Have Robot move forward for 1 second, turn right about 90 degrees move forward 1 second turn left about 90 degrees move forward Stop beep three times Do the above in reverse Read pages 773 - 785 in your text Answer the following questions. Describe your robot's environment. What type of "real world" tasks might a robot like the one you've built be good for? What types of effectors does your robot have and what are they used for? How many actuators does your robot have? Describe your robot's actuators. What is a nonholonomic robot? What is a holonomic robot? Which one of these describes your robot? Is your robot statically stable or dynamically stable? Why? Our robots have very simplistic sensors. Choose one sensor type, as described in your text, and describe how it could be used to help solve the your robot 's problem task. (6 points)
	Task 2 - Have the robot use its photo sensors to follow a path. The path is defined by silver tape on a black background. (2 points)
	Task 3 - Use the neural network software you created to teach your robot how to follow a path. Evaluating the performance of an intelligent agent allows one to improve the agent. Did your robot follow the track better when trained with a neural or when it was hard programmed? (2 points)
	Extra Credit - Have robot move forward until it detects that it bumped into an obstruction.(Use touch sensors). When this happens the robot will turn right and then move backward. When it bumps into an obstruction the robot will turn right and then move forward again. (2 points)
	Extra Credit - Use decision tree software to teach your robot how to follow a path. Compare the decision tree solution to the neural net solution. Which performed better? What reasoning can you give for any differences? If they performed equivalently, what reasoning can you give for this?(2 points)
Total Score: