Project On Evolving neural robot

The Project is to build a mobile robot with a developed neural network such that it evolves to avoid collisions into a circular vertical white wall while traveling at the fastest speed and straightest line possible without human intervention or external computers.

The completion of this project required extensive capacity and application on both hardware and software ends. In constructing the robot, we needed to build the custom prototype board, apply infrared sensors as neural inputs, implement stepper motors for robot motion, and provide a mobile power supply to the MCU. The purpose of these design factors is to allow the autonomous movement of the robot while minimizing the size of our robot, to accurately sense distance and collisions into the white wall of our arena, and to calculate the velocity precisely while providing sustainable torque to move our robot. On the software end, we needed to execute an evolutionary spiking neurons algorithm that interfaced with our hardware. The purpose of this was to integrate a spiking neural model with infrared sensors as inputs and motor speeds as outputs to determine robot velocity and direction. We also implemented the evolutionary model based on assessing random individuals of a randomly generated population through a fitness equation and improving the population by discarding the worst individual in the population with the worst fitness. The fitness equation measured by the velocity of the robot, the direction change, and the amount of activity from sensors. 
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Robotic Vacuum Cleaner Project

The robotic vacuum is mainly built from a circular piece of foam board.. The robotic vacuum uses a rotating brush underneath the unit to vacuum a carpet as it passes over it. Two stepper motors, aligned across the center axis of the robot, are used to accurately drive the robotic vacuum around a room. Because the body of the robot is circular and the steppers are placed along the center axis, the robot can spin in place in any direction. One free-spinning chair wheel is located at the rear of the robot to keep it balanced.

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Project On autonomous Visually Steered Car

For our final project, we re-engineered a remote control car to autonomously navigate through a track by detecting lanes and centering itself between them as well as detect objects in front of it and avoid collision. The RC car detects lanes through image input from a low-resolution camera mounted at its front. Using an IR distance sensor, the car determines when to stop accelerating once a certain distance between a forward object has been breached. All computations based on sensor data are handled by an Atmel Mega644 MCU. Due to the nature of the input peripherals, especially the camera, this system is extremely time sensitive so that computations had to be optimized as much as possible in order for the car to be able to react and respond with proper movements in real time. In addition, given the limited computational capacity of this 8-bit MCU, our design made use of several computational efficiency strategies. 
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