If you participate in this competition you’re effectively giving free research to a weapons company who will use it to improve their killer drones. I’m not judging but that’s what this is. Please correct me if I’m wrong, but I don’t think I am.
I only say this because technologists sometimes don’t think about the reasons behind things, they just see a fun problem to solve.
Anduril is far ahead of anything we can produce here for this competition, but it's certainly a great method for them to identify potential talent who can bring needed skills to their team, hence the grand prize of a job offer. The terms of the competition is they get to use any submission for marketing purposes but the IP remains with the participants. Personally I'm in the camp that the world has bad guys, and they are building technology too. Smartest to make sure yours is better. Professionally we only work on defensive systems, which are in high demand these days.
the included baseline just demonstrates that the Betaflight controller will indeed move to the hard-coded center positions of each gate. So the basic first solver task would be to replace that with a CV or ML inference based approach. We plan to add another demo solver into the sample set that shows this next, currently in progress.
Both great tools, optimized for slightly different needs. Gazebo is great for simulation and testing of higher level control, or for simulation that doesn't require 1000hz sensor simulation rate. Nvidia Isaac focuses on ML model training workflows, not ideal for interacting directly with your flight software for flight testing your code before you fly. This aims to be software CI/CD for your drone builds.
If you participate in this competition you’re effectively giving free research to a weapons company who will use it to improve their killer drones. I’m not judging but that’s what this is. Please correct me if I’m wrong, but I don’t think I am.
I only say this because technologists sometimes don’t think about the reasons behind things, they just see a fun problem to solve.
Anduril is far ahead of anything we can produce here for this competition, but it's certainly a great method for them to identify potential talent who can bring needed skills to their team, hence the grand prize of a job offer. The terms of the competition is they get to use any submission for marketing purposes but the IP remains with the participants. Personally I'm in the camp that the world has bad guys, and they are building technology too. Smartest to make sure yours is better. Professionally we only work on defensive systems, which are in high demand these days.
Does the starter kit include a simple baseline agent (like a basic line-follower) that I can run immediately to see how the simulator works?
the included baseline just demonstrates that the Betaflight controller will indeed move to the hard-coded center positions of each gate. So the basic first solver task would be to replace that with a CV or ML inference based approach. We plan to add another demo solver into the sample set that shows this next, currently in progress.
Looks cool! But why not just use Gazebo? Or Issac?
Both great tools, optimized for slightly different needs. Gazebo is great for simulation and testing of higher level control, or for simulation that doesn't require 1000hz sensor simulation rate. Nvidia Isaac focuses on ML model training workflows, not ideal for interacting directly with your flight software for flight testing your code before you fly. This aims to be software CI/CD for your drone builds.
Wow.That's looks great.