Agenda

• Stage 1: 10 mins -Introduction to Embedded Systems and Self-driving Cars
• Stage 2: 10 mins -Introduction to software, tools, and languages.
• Stage 3: 25 mins - Basics of sensor fusion.
• Stage 4: 25 mins - Introduction to Embedded Systems and selection of controllers for standalone applications
• Stage 5: 25 mins - Introduction to mapping and path planning in self-driving cars.
• Stage 6: 15 mins - Embedded Systems in Active Safety systems
• Stage 7: 10 mins Briefing on career opportunities and upskilling in the field of Embedded Systems in self-driving cars.

Tools Used: Python - Language, Embedded C, Raspbian OS, and Computer Vision libraries. Jupyter Notebook - IDE (Integrated Development Environment)

Learning Outcomes

At the end of the workshop, the learners will be able to:

• Understand the basics of sensor fusion using embedded systems.
• Interpret the integration for standalone applications using Embedded devices.
• Understand various API's to address self driving car applications.
• Understand the importance of tiny machine learning over standalone embedded devices.

Instructor Details

1. A.JEGAN

Total years of working experience: 11+ years 

Educational Qualification: M.Tech in Automotive Electronics (PSG College of Technology)

Previous companies: RNTBCI, KPIT Technologies, SRM, TCS Ltd.

Short Bio: MBD-Delivery Lead/Sr. corporate Educator with 11+ years of Experience spanning from academia to corporate, as an academician I have guided a funded project in building a formula student electric race car and participated in FSAE Italy 2015, and FORMULA GREEN 2017 India. I have established an Automotive Electronics and control research laboratory focusing on Rapid control Prototyping and Hardware in the loop simulation in association with Mathworks and NI system. As a Senior Educator I have developed a competency framework for meeting the needs of the Automotive Business Unit in verticals such as Embedded Systems, AUTOSAR and Model-based development, as a delivery lead, I have managed transversal team with owning the responsibility of developing tools used in EMS Software development. 

Role In Skill-Lync: Associate Director (Embedded)

2. Dadi Ravikanth is currently a Senior Technical Support Engineer in Autonomous Vehicles at Skill-Lync. He has 7+ years of experience in the field of Robotics and Automation. He has worked as Assistant Professor for 6 years at Manipal Academy of Higher Education educating students on topics such as ROS, Localization and Mapping, Embedded Systems for Machine Learning, Predictive Algorithms, and Open Computer Vision. He specializes in Haptics and perception psychology and has published SCI & Scopus journals in the field of perception psychology for applied sciences.