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Graduation project repository, Real-time vehicle detection using two different approaches. HOG+SVM traditional approach and Deep Learning based approach using state of the art YOLO convolutional neural network.
Esse projeto consiste em simular um veículo autônomo que identifica obstáculos através de um sensor ultrassônico que mede a distância e define a melhor rota e um infravermelho que identifica objetos, degraus e depressões, possibilitando-o desviar dos mesmos. A programação do robô foi desenvolvida utilizando a linguagem C no software de desenvolv…
The Autonomous Track Exploration & Navigation Algorithm enables a self-driving car to efficiently explore, map, and navigate a predefined track using real-time sensor data. It employs ultrasonic sensors, IMU, and wheel encoders to detect obstacles, track movement, and optimize navigation.