Formula Bharat Driverless Vehicle Course

Explore the world of Autonomous Vehicles

What you'll learn

Advanced data analysis and AI/ML, Radar antenna design and implementation, ADAS, Advanced simulation to assist DV development.

Path Planning and trajectory control with visual cone detection, Getting started with ROS.

Real-time simulation using Typhoon HIL.

Simultaneous Localization and Mapping (SLAM) and Sensor Fusion.

Creation of Real-world environment in simulations.

Understanding modern time autonomous technology, cybersecurity, functional safety, deep learning and computer vision algorithm.

Requirements

Basic understanding of Automobile technology, AI/ML, ROS, and Sensors.

Interested to learn about autonomous vehicles and technology

Description

Are you struggling to understand the complexities of driverless vehicle? Are you finding it challenging to design a compliant autonomous driving system? Are you finding it difficult to efficiently plan and manage your autonomous vehicle project? This course is here to eliminate those concerns.What You'll Learn:Advanced data analysis and AI/ML, Radar antenna design and implementation, ADAS, Advanced simulation to assist DV development.Path Planning and trajectory control with visual cone detection, Getting started with ROS.Real-time simulation using Typhoon HIL.Simultaneous Localization and Mapping (SLAM) and Sensor Fusion.Creation of Real-world environment in simulations.Understanding modern time autonomous technology, cybersecurity, functional safety, deep learning and computer vision algorithm.Experience of FS Teams.Various available software for driverless.Course Highlights:Understanding Autonomous vehicles with the technology used in the current world.Comprehensive coverage of Engineering used in the development of Autonomous Vehicles on software stack, including - - Data analysis and Machine learning - ADAS Radar sensor and Communication Antenna - Simultaneous Localization and Mapping (SLAM) - Real-time simulation using Typhoon HIL - ROS and Sensor Fusion - Modern day autonomous vehicle technologyProgram Basis: The course contains sessions from industrial experts working in automobile and autonomous systems. This course does not contain any rule adaptation of the formula student driverless categoryCourse Outcome: By the end of this course, you will be able to develop your software stack for autonomous vehicle using various tools and software.

Overview

Section 1: Altair

Lecture 1 Introduction to the Speaker

Lecture 2 M1-Integrated system-of-systems simulation connecting 0D, 1D & 3D co-simulations

Lecture 3 Introduction to the Speakers

Lecture 4 M2 - Advanced data analytics & AI/ML to enable Real time Digital Twins

Lecture 5 Introduction to the Speakers

Lecture 6 M3 - Radar Antenna Design and Integration

Lecture 7 M4 - Virtual Drive Tests for ADAS Radar Sensors and Communication Antennas

Lecture 8 Introduction to the Speaker

Lecture 9 M5 - Embedded System Design & Open Vision for ADAS

Lecture 10 Introduction to the Speaker

Lecture 11 M6 - Advanced Simulations to Assist Development of Autonomous Vehicles

Section 2: Typhoon HIL

Lecture 12 Introduction to the Speaker

Lecture 13 M1 - Real time Simulation and its Application in E-mobility using Typhoon HIL

Lecture 14 Introduction to the Speaker

Lecture 15 M2 - Real time Simulation and its Application in E-mobility using Typhoon HIL

Lecture 16 M3 - Real time Simulation and its Application in E-mobility using Typhoon HIL

Lecture 17 Introduction to the Speaker

Lecture 18 M4 - Real time Simulation and its Application in E-mobility using Typhoon HIL

Lecture 19 M5 - Real time Simulation and its Application in E-mobility using Typhoon HIL

Section 3: Bosch Global Software Technologies Private Limited

Lecture 20 Introduction to the Speakers

Lecture 21 M1 - Robot Operating System (ROS) for Autonomous Driving

Lecture 22 M2 - Robot Operating System (ROS) for Autonomous Driving

Lecture 23 Introduction to the Speakers

Lecture 24 M3 - Mapping and Localization

Lecture 25 Introduction to the Speakers

Lecture 26 M4 - Mapping and Localization

Lecture 27 Introduction to the Speakers

Lecture 28 M5 - Sensor Fusion in Autonomous Driving

Lecture 29 M6 - Sensor Fusion in Autonomous Driving

Section 4: MathWorks

Lecture 30 Introduction to the Speakers

Lecture 31 M1 - 3D Scenes for Automated Driving

Lecture 32 Introduction to the Speaker

Lecture 33 M2 - Visual Detection of Cones

Lecture 34 Introduction to the Speaker

Lecture 35 M3 - Path Planning and Trajectory Control of Autonomous Vehicles

Lecture 36 About the software and introduction to M4

Lecture 37 M4 - Getting started with ROS in MATLAB and Simulink

Section 5: Hexagon

Lecture 38 Introduction to the Speaker

Lecture 39 Module 1

Lecture 40 Module 2

Section 6: Meet the FS Teams

Lecture 41 Introduction to the Speaker - KA-RaceIng

Lecture 42 M1 - Overview of AS System and Keep it simple

Lecture 43 M2 - Adaptive Velocity planning, together with velocity estimation

Lecture 44 Introduction to the Speakers - e-gnition Hamburg

Lecture 45 M1 - Team Management & showcase autonomous steering actuation

Lecture 46 Introduction to the Speakers - e-gnition Hamburg

Lecture 47 M2 - Overview of autonomous Formula Student software stack & Safety in FS DV

Section 7: Additional sessions

Lecture 48 Introduction to the Speaker

Lecture 49 Introduction to Autonomous Driving & Design of Modern Automotive HMi

Lecture 50 Introduction to the Speakers

Lecture 51 Role of Vehicle Integration in development of Autonomous Vehicle

Anyone interested to learn about automobile, autonomous vehicle technology.,Anyone who is part for Formula Student DV Cup category.,Anyone who will be joining Formula Student DV Cup category.