Aggressive Maneuvers for Autonomous Quadrotor Flight

What people said

CrabDude · 2011-01 · Recommendation

The simple matter is that the implications of these drones reaches far beyond simply building things, like showing one aspect of what a hammer can be used to build. The real takeaway is the radical increase in the abilities of flying drones, and the raw potential they leave to be harnessed by future engineers and entrepreneurs. Those who discount their usefulness by staying within the context of the video, and not elaborating outside of that, aren't getting it. I would refer you especially to @burgerbrain's comment and the videos he posted. Specifically: [VIDEO]

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gene-h · 2017-05 · Reference

I wonder how well the learned policy generalizes to other environments. Places like an art gallery, outside, or a cave. Could the network have learned something fundamental about monocular vision? It would also be interesting to see if the learned policy corrects for perturbations. If we tilt the drone by hitting it, will the policy stabilize it again? While this is a really cool result, I suspect that this approach might not be the best way to control UAVs. Dragon flies are ready to fly, avoid obstacles, perch on stuff, hunt down prey right after warming up their wings for the first time. This implies that a good amount of the flight behavior is 'hard-coded.' Although I really can't wait until someone expands upon this approach. So instead of outputting left or right, the network could output 'stick vectors,' which translate to control stick commands. Maybe even have the network take in some sensor data and a 'move in this direction' vector. Add in a pinch of sufficiently fast video processing and we could probably learn how to do fly through an FPV course or do aggressive maneuvers to fly through someone's windows[0] [0] [VIDEO]

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TeeWEE · 2013-12 · Reference

I believe this is possible. Just look at these autonomous drones doing stunts: [VIDEO] Delivering a packet is much easier than the stuff the are doing in this vid.

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