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design_patterns_for_self-driving_automation [2017/04/23 22:54] (current)
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 +====== Design Patterns for Self Driving Automation ======
 +
 +**Introduction**
 +
 +This is the first steps at curating a set of design patterns in the field of self driving automation.
 +
 +I am hoping that this becomes a collaborative endeavor. ​ The development of Design Patterns has historically been intertwined with the employment of a Wiki.  In fact, one of the earliest Wikis, which likely pre-dates Wikipedia, was invented for the sole purpose of documenting Design Patterns.  ​
 +
 +//
 +The WikiWikiWeb is the first ever wiki, or user-editable website. It was launched on 25 March 1995 by its inventor, programmer Ward Cunningham, to accompany the Portland Pattern Repository website discussing software design patterns.//
 +
 +The idea is that Design Pattern development is always a collaborative endeavor.  ​
 +
 +Self-Driving Automation is an entirely new field. ​ It is usually described as Self-Driving Cars.  Knowledge in this space is in its infancy and what better opportunity to start building a Design Pattern repository than in an emerging field. ​ It is not only emerging, but also a complex field that involves the integration of a lot of different technologies and the real-time orchestration of these integrations. ​  I hope in the next several months to be able to capture the knowledge into a form that is digestable by future practitioners.
 +
 +The motivation as to why I use the word "​Automation"​ rather than "​Cars"​ is that I am seeking a more general application of this technology. ​ A very glimpse of this idea of an automation that employs Deep Learning, Vision, Sensor Fusion and a whole lots of other technologies can be found in Amazon Go.   ​Amazon Go isn't a car,  it is a self-service retail store! ​  
 +
 +https://​www.wired.com/​2016/​12/​amazon-go-grocery-store/​
 +
 +//As for how its “Just Walk Out Shopping” experience works, Amazon seems emphatically not to want to share details. It steeps its description of how the system works in buzzwords: computer vision, sensor fusion, and deep learning. It uses sensors throughout the store and artificial intelligence to tell which direction customers are looking, even in a crowd, and can identify partially blocked labels. Beyond that, details are hazy.//
 +
 +The concepts found in self driving cars, I believe is also transferrable to many other fields that have complex sensory environments and require realtime decision making.
 +
 +
 +[[sda:Deep Learning]]
 +
 +[[sdd:​Vision]]
 +
 +[[sda:​Sensor Fusion]]
 +
 +[[sda:​Localization]]
 +
 +[[sda:​Control]]
 +
 +[[sda:Path Planning]]
 +
 +[[sda:​Orchestration]]
 +
 +**Resources**
 +
 +https://​github.com/​OSSDC/​awesome-autonomous-vehicles
 +
 +https://​arxiv.org/​pdf/​1612.03653v1.pdf Learning to Drive using Inverse Reinforcement
 +Learning and Deep Q-Networks
 +
 +https://​arxiv.org/​pdf/​1704.05519.pdf Computer Vision for Autonomous Vehicles:
 +Problems, Datasets and State-of-the-Art
 +
 +Seeking your expertise, sign up at: https://​www.linkedin.com/​groups/​8584076
 +