harshnehal1996/Self-Driving-Vehicle-With-Carla
This repository contains implementation of reinforcement learning based driving agent in Carla aswell as Localization and Mapping in C++
This project helps automotive engineers and researchers develop and test self-driving car algorithms in a simulated environment. It takes simulated sensor data (like camera, LiDAR, and IMU) from the CARLA simulator as input and produces either a trained reinforcement learning agent for autonomous driving, a detailed 3D map of the environment, or a localized path showing where a vehicle is within that map. This is ideal for those working on autonomous vehicle perception and control.
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Use this if you need to experiment with and evaluate self-driving car control or perception systems, such as mapping or localization, in a realistic simulation without needing a physical car.
Not ideal if you are looking for a plug-and-play solution for real-world autonomous vehicles, or if you don't have access to or experience with the CARLA simulator.
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Python
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Oct 19, 2023
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