Assignment Task:
Overview of the Task
The file left_wall_follower.fis contains a Fuzzy Inference System (FIS) that can be used as a controller to guide the simulated robot successfully around the test environment. This file and a version of FIS_navigate.m that uses it as a controller can be downloaded from Student. This FIS can be used to generate training data for a neural network. Your main task is to design, train and test a neural network that can generate appropriate actuator outputs when being presented with sensor inputs. This trained network can then be used as a controller and demonstrated in the KiKs simulator.
Questions to Consider in Your Experiments
During this investigation, you should consider and investigate (at least) the following questions:
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Get Help Now!- What is the best way to generate the training data?
- What type of neural network should you use?
- How many layers should you use?
- What transfer functions should you use for each layer?
- Does the training data have to be “normalised” to give input and output values that are in appropriate ranges for the neural network?
- How many neurons should you include in each layer (particularly any hidden layers)?
- What training algorithms should you use?
- Does the network show any signs of overfitting, with the corresponding poor generalisation?
- How well does the trained neural network work as a controller for the robot?
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