Learn How To Build Your Own Self-Driving Car
Channel: Engineers.SG
Date: 30/08/2018

Learn and build your own autonomous driving algorithm using the latest computer vision techniques and Python!

Computer Vision is a novel interdisciplinary field that can be applied to numerous tasks, especially those related to automation such as image search, robotics, drones automation, self driving cars or video information extraction, among others. There is an exponential growth in the application of Computer Vision into our daily tasks, therefore the growth on market need for employees with this knowledge. According to Glassdoor the average salary of a Computer Vision Engineer is more than $110,000 -  that even increases when you add some Deep Neural Networks knowledge to it.

Self driving cars is a rapidly growing industry that has one of its nerve centers in Singapore. The number of companies that have invested in development of car automation keeps growing. Efforts made by companies and research institutes like Uber, Google, nuTonomy, A*STAR, Tesla, NUS/MIT and others are proof of the fast growth of this field. Singapore constitutes a world leading hub for this technology, hosting top companies and research institutes along with state of the art test field environments. According to smartnation.sg self driving vehicles are the future of mobility in Singapore, having the potential to radically transform our transport system and improve our living environment in many areas such as safety, efficiency, reduced fuel consumption, and traffic reduction. Wouldn’t you want you like to be a part of this change? Learning the computer vision skills needed for this type of development will get you closer to this hot market area and will open more interesting opportunities for your career path.

During this workshop we will introduce the main computer vision libraries and their purposes. An overview on how to use these libraries and their documentation will be given so you can continue your learning process in this field. Finally, using this techniques a self driving algorithm will be built for our car driving through the streets of Singapore. 

At the end of this workshop you will:
Know the main computer vision libraries and their purpose
Know where to find documentation
Be able to produce tools using these libraries and their algorithms
Have built a real world self driving car algorithm and tested it with real data from the streets of Singapore

Note: Basic knowledge of Python is required. Bring along your laptop so you can take your own autonomous driving algorithm home!

Speaker: 
Marco A. Gutiérrez is a PhD holder in cognitive vision planning for robotics systems and co-founder of GlideX, a startup in the field of AI for network security.

In 2015, he was granted the ARAP scholarship at the A*STAR I2R Human Language and Technology Department. Among his recent awards is the merit award at the “Singapore Challenge: The Science of Future Cities“. He was also finalist at the Entrepreneurship Forum and Start-up Competition (EFSC) at the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'15) and received the merit award at the NVIDIA Jetson Developer Challenge for Artificial Intelligence.

Dr Marco has contributed to several free software robotics and AI related projects like RoboComp, the Point Cloud Library and Open Perception. He also served as organization administrator and mentor for these projects on several editions of the Google Summer of Code programme.

His areas of interest include cognitive vision, artificial intelligence, embedded systems and free software.

Event Page: 
https://www.upcodeacademy.com/instructors/9/courses

Presentation Jupyter Notebook and code:
https://github.com/marcoag/lanes_detection

Live interactive demo of presentation:
cv.marcogg.com

Produced by Engineers.SG

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