Neural Networks for Flight Control

Flying robot armed with shotgun
flight controller and

 

Something I just submitted to slashdot:

A small company called Neural Robotics has produced a robotic mini-helicopter armed with a rapid-fire shotgun. Based on their low-cost AutoCopter, the UAV uses neural network-based flight control algorithms to fly in either a self-stabilizing semi-autonomous mode controlled by a remote operator, or a fully-autonomous mode which can follow GPS waypoints. A video of the AutoCopter Gunship is available. (Dijjer mirror)

Stepping aside the ethical issues of replacing soldiers with flying shotgun-wielding robots for the moment, their “neural network-based” flight control system seemed like an interesting technical accomplishment. This PDF briefing has a few details.

Taking a look at page 14 of their PDF though, perhaps their control system is a little on the simplistic side. It seems to just update roll and pitch based on the current movement and facing of the helicopter, without making use of visual information or other sensors. I’m not too familiar with flight control, but using a neural network for that seems like overkill. When in fully-autonomous mode, I wonder if they make use of sensors for crash-avoidance at all, or if they just hope that nothing’s in the way of the chosen GPS coordinates.

Source: Edge of Vision

Springer Fully Tuned Radial Basis Function Neural Networks for Flight (The International Series on Asian Studies in Computer and Information Science)
Book (Springer)

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