shitals

TLDR; The idea of the new system is to turn Apple’s existing network of iPhones into a massive crowdsourced location tracking system. Every active iPhone will continuously monitor for BLE beacon messages that might be coming from a lost device. When it picks up one of these signals, the participating phone tags the data with its own current GPS location; then it sends the whole package up to Apple’s servers.

I'm a member of this project. We are trying out few new ideas and your feedback and comments would be awesome! If you have been using TensorBoard, Visdom etc then you would probably find this work useful. Please let us know any questions you have.

Not if you have simulator :)

https://github.com/microsoft/airsim

Not quite... I think Udacity's simulator is built on Unity and the environment it runs in is probably not as big and detailed.

TLDR; AirSim is simulation software built upon Unreal Engine 4 from Microsoft Research. It now includes car simulation and real city-like environment where you can test your self-driving algorithms. You can just download the binaries and start calling its Python APIs in minutes.

I'm the lead developer on the AirSim team. Please let us know if any questions!

We at Microsoft Research have been developing this: https://github.com/microsoft/airsim. It has car model to test self-driving algorithms.

Want to work on AI + Robotics at Microsoft Research, Redmond, WA? Does Aerial robotics, Unreal engine, physics, building low level firmwares excites you? You will need to have demonstrable great C++ coding chops, passion for tinkering, ability to get into unknown areas fast and great CS algorithms design skills. Any experience with Unreal Engine, Unity, Physics engines, robotics, drones, firmwares, deep learning etc would be big plus as well. We have already shipped AirSim[1] and we are excited to take it to next level and advance state of the art in reinforcement learning among other things!

The position requires US work authorization and interviews would be in-person at Redmond, WA. Please send resumes at shitals@micro####.com.

[1] https://github.com/microsoft/airsim

Want to work on AirSim [1] as contractor at Microsoft Research, Redmond, WA? Does AI, Aerial robotics and drones excites you? You will need to have demonstrable great C++ coding chops, passion for tinkering, ability to get in to unknown areas fast and great CS algorithms design skills. Any experience with Unreal Engine, Unity, Physics engines, robotics, drones, deep learning etc would be big plus as well. Send resumes at shitals@micro####.com.

[1] https://github.com/microsoft/airsim

You can and I'd set that up at least once successfully but it isn't easy. I've created a doc for this here: https://github.com/Microsoft/AirSim/blob/master/docs/sitl.md

Yes, we are supporting to get telemetry as well as ground truth. We also support multiple vehicles but you will need to then build your controller for them or set up multiple HITL/SITL flight controllers.

It is Unreal plugin! https://github.com/Microsoft/AirSim/blob/master/docs/build.m...

Yes! We have been fortunate to find few in-house drone racers and learning the grit behind their skills. Getting SITL/HITL with Betaflight and/or Cleanflight is definitely one of our important goal in coming months.

You are absolutely at the right place. We have gone to extra length to design our code so that vehicle specifics are abstracted away behind interfaces. Also things are easily switchable. For example, don't like our physics engine, bring your own! As mentioned in release notes, we are working on other vehicle types. However water based crafts are not on our radar. My guess would be that physics would be more expensive and less accurate in general for water based vehicles.

We would love to connect and see how community is using this. Join our FB group and we can take it from there: https://www.facebook.com/groups/1225832467530667

This is not Robotics Studio. It's a simulator for training and testing deep learning/reinforcement learning algorithms for autonomous vehicles. However we are sure community will find other uses :).

We are conducting experiments for transfer learning. Stay tuned! For laser tag mode, we will leave it to the community :).

That's correct :). The NVidia 1080 yields FPS of ~23 with all 3 views in real time!

We are internally able to compile the core (AirLib) however there are few rough edges and also we want to make sure Unreal also works as expected on Linux with our plugin.

We are not officially supporting Mac yet, but contributions are welcome :). Our code is cross platform and given enough efforts, I think it can be made available on pretty much any platform. One thing to think about is GPU requirements. Even moderate environments in Unreal can easily require GPUs with at least 4GB RAM.

Yes, that's on our plan. Stay tuned. Please also feel free to join our FB group if you had like notifications: https://www.facebook.com/groups/1225832467530667

One of our major focus is to use AI in real world. A lot has been done in applying AI to video games but we are still taking baby steps in applying it in real world. The question that we want to answer is this: can we train and test algorithms in simulated world and then use them in real world? This is known as transfer learning problem and its a huge area of research where people are investigating, for example, how can we use 80% simulated data and 20% real world data? The games typically found on commercial market are created for entertainment purposes. For example, game creator might decide to cheat on physics to optimize performance and may configure things so its easy but not too easy. Our focus was rather to pursue good physics, sensor models, vehicle dynamics, hardware-in-loop and so on. Also, we wanted to make this project as open source. Most commercial products typically involve complex chain of 3rd party licenses that almost make it impossible for them to be open source.