Self-Automated Car with Obstacles Detection

Abstract

In this paper, we proposed a self-automated Robot chassis car along with an obstacle detection technique. The main idea behind this paper is to reduce collision that occurs from accidents on roads. To achieve this, several methods are performed such as lane, stop sign, and object detection. It contains various terminology based on deep learning to perform image processing and machine learning. To determinewe had used a pi camera attached to the raspberry pi board to collect input images to steam data over a server. In our case laptop will acts as a server. Here, a neural network and Haar-based cascade classifier are used for obstacles detections. In addition to this, our designed model incorporates self-controlling such as left-right turn, forward-backward turn, and U-turn based on Arduino commands. In a nutshell, the proposed model helps humans to reduce efforts and improve safety along with collision avoidance.