Autonomous System Infrastructure

    Autonomous System Infrastructure

    WINLAB Summer Internship 2022

    Group Members: Steven Tan, Meghana Achyutananda, Anitej Thamma, Arunima Suri, Pranav Manikonda, Suhani Sengupta

    Project Objective

    Develop a server-client infrastructure to allow for remote control of autonomous robots in the orbit smart city environment. Students will begin by setting up ROS on a robotics platform at Winlab so that they have a system to work on, with the ultimate goal of testing the autonomous driving system on the hardware developed by the smart car team at the end of the summer. In addition to working on the server-client system and measuring the latency of the system, students will research and implement different self-driving algorithms and test them with the ROS platform. Most of this work will be done using python and pytorch (a machine learning library). Students will also need to implement methods for collecting data in order to train their self-driving systems.

    Background Material

    This project will use Robot Operating System (ROS) and pytorch. Students should familiarize themselves with ROS and pytorch. For a look at a simple self-driving system that could be implemented as a place to get started, you can read this paper on machine learning for self driving. For a better understanding of machine learning, these course notes are a very helpful resource.

    Last modified 23 months ago Last modified on Aug 10, 2022, 3:13:28 AM
    Note: See TracWiki for help on using the wiki.