Design and Implementation of Autonomous Car using Raspberry Pi
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The project aims to build a monocular vision autonomous car prototype using Raspberry Pi as a processing chip that is capable of reaching the given destination safely and intelligently thus avoiding the risk of human errors.Abstract:
The project aims to build a monocular vision autonomous car prototype using Raspberry Pi as a processing chip. An HD camera along with an ultrasonic sensor is used to provide necessary data from the real world to the car. The car is capable of reaching the given destination safely and intelligently thus avoiding the risk of human errors. Many existing algorithms like lane detection, obstacle detection are combined together to provide the necessary control to the car.read more
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Lane detection and tracking using B-Snake
TL;DR: A robust algorithm, called CHEVP, is presented for providing a good initial position for the B-Snake model, and a minimum error method by Minimum Mean Square Error (MMSE) is proposed to determine the control points of the B -Snake model by the overall image forces on two sides of lane.