Why DeepRacer?

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Revision as of 15:43, 25 October 2019 by Tptak (talk | contribs) (Initial content)
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ARCC have studied alternatives for learning and teaching DeepRacer

Pros[edit]

  • Integrated Approach
  • Simulation Based - No expensive car or track required
  • Abstracts most of the software: Allows the developer to focus just on the RL model
  • Competition - Unifies community into large scale competition
  • Active development community
  • Standardized car, race is just about software
  • Uses ROS on backend

Cons[edit]

  • AWS platform can get expensive
  • Not much flexibility in ML models, you're stuck with PPO

AWS DeepRacer Alternatives[edit]

There are a few other alternatives to the AWS DeepRacer if you're looking to race autonomous cars

Donkey Car[edit]

The Donkey Car is a community project to opensource self driving cars. They also offer kits to build the car seperately. All in all, the car cost around $250, which prices it lower than the DeepRacer. Theres also no standardization in cars, every car has a different chasis and motors, meaning hardware matters just as much as software. Additionally, DonkeyCar isn't supported by an organization like Amazon, so it's a little more spread out and not as organized compared to DeepRacer.

Pros[edit]

  • Actually cheaper
  • Completely Open Sourced
  • Pretty Large Community

Cons[edit]

  • Community isn't as big as AWS DeepRacer
  • Competitions are spread out
  • No simulator to test and develop in, requires large track

Custom Built Car[edit]

The group I work with, ARCC, built a self driving car from scratch using a Traxaas RC car, NVIDIA Jetson TX2, and Intel Realsense camera. This was our first project in autonomous cars, and we still develop on it with alternative algorithms and methods.

Pros[edit]

  • Fast
  • Much more powerful hardware
  • Fully customizable - Choose whatever hardware or software stack you want

Cons[edit]

  • Hardware problems to debug :(
  • Much more expensive
  • No community support as it's a oneoff
  • Too big for most tracks, we race it on a 400m running track

F1tenth[edit]

Pros[edit]

  • Fast
  • Much more powerful hardware
  • Customizable - Choose whatever hardware or software stack you want

Cons[edit]

  • Much more expensive