Artificial intelligence based position locator using ultrasonic sensors

This job consists in the implementation of an Artificial Intelligence Based Position Locator that use Ultrasonic Sensors and is integrated in the structure of a small mobile robotic car. The system includes an Arduino computer and a self-motivated artificial neural agent capable to learn by itself how to move the robot safely around, in a real world platform with scattered obstacles. The robotic platform comprises batteries, ultrasonic sensors, motors, wheels etc. And is subjected to mechanical ambient noise cause by the motors inertia, wheels’ displacement friction and sensors imprecision. A reinforcement learning (RL) agent drives the robot in its learning pase and extract knowledge about how to move in a real world situation. During the learning phase, knowledge is stored in a trainable local neural network that runs in real time in the local Arduino computer board and learns the policy required to move the robot. This net is balanced trained as to satisfy the move ahead condition required by the a free moving robot. During the operation phase, the robot uses the learned policy stored in the neural net and behaves as a Markov decision process.

• Autore principale: Montenegro Cárdenas, Jordan Rodrigo (author)
• Natura: bachelorThesis
• Lingua: eng
• Pubblicazione: 2021
• Soggetti: Robots; Autoaprendizaje; Evasión de obstáculos; Self-taught; Obstacle avoidance
• Accesso online: http://repositorio.yachaytech.edu.ec/handle/123456789/413