Adrenaline Fueled Development: Racing With Autonomous Vehicles · [email protected]...
Transcript of Adrenaline Fueled Development: Racing With Autonomous Vehicles · [email protected]...
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DATE
Adrenaline Fueled Development: Racing With Autonomous VehiclesSession: 23317
Jendrik Jördening Anthony NavarroData Scientist Product LeadAkka Technologies [email protected] [email protected]
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The ProgramUdacity launched the world’s only Self-Driving Car training program in November 2016 receiving over 15,000 applications for this Nanodegree program!
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The ChallengeUdacity teamed up with PolySync to sponsor a team to participate in the Self-Racing Cars event at Thunderhill Raceway, California on April 1-2, 2017.
The challenge was to send a Kia Soul, provided by PolySync, around Thunderhill Raceway autonomously using only a single camera and GPS as sensors.
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The TeamA team of 17 Self-Driving Car students came together on February 15th to participate in the race and represent Udacity and PolySync.
The international team was represented 5 different countries from diverse backgrounds with two things in common: a love for learning and self-driving cars!
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Development Phases
weeks to work as a team
days of on-site development, training, and integration
hours of adrenaline fueled racing and coding
Only possible with GPU computations powered by GTX 1070
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Preparation● Build a simulator for the
thunderhill race track● Examined Polysync Car Sensor
Samples● Trained and Tested Neural
Networks● Discovered big difference
between Real and Simulation Data
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29th March – Meet & Greet
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30th March Morning – First Day on the Track Race Track●
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30th March Evening – Turn, Baby, Turn!
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31st March – Double Failure (Brakes and Steering)
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31st March 4 p.m. – Testing the first models
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1st April 9 a.m. - Race Day 1 Master One Turn
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Results
Made it around all turns autonomously! ...but not in one lap
● How to deploy a real end-to-end deep neural network on a car● Integrating physical systems can be difficult● Reality and simulation are completely different things● Hybrid team from students and industry can benefit each other a lot!● Nothing can replace the real-world experience● Such events are the greatest networking opportunities
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Path Forward - ROS Bridge and SegNet
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Semantic Segmentation Utilising a U-Net and Feature Extraction from Yolov2 @Akka
Credit: M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele, "The Cityscapes Dataset for Semantic Urban Scene Understanding," in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition
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THANK YOU FOR YOUR ATTENTION
Jendrik Jördening Anthony NavarroData Scientist Product ManagerMailto: [email protected] Mailto: [email protected]
The full story:
Our Very Own Grand Challenge