About Neural Robotics
The AutoCopter system uses proprietary neural-network flight control software that provides unsurpassed stability in hover and flight modes, as well as ease of use for operators. A helicopter is an inherently unstable platform that requires continuous monitoring and input to remain under control. However, the neural network systems developed by NRI mimic the human brain in that they can learn and adapt to new circumstances for which there has been no previous “experience." This allows the AutoCopter to stabilize itself, even through changes in weight, wind speed, and direction.
An optional three-axis motorized gimbal provides a controllable platform for a variety of sensors including video, IR, and still cameras, as well as spectrometers and other measurement devices. Sensor data can be transmitted real-time to the user via broadband RF. Basic avionics components, included with the AutoCopter, consist of a PC/104 computer, attitude and heading reference system, referred to as AHRS, GPS receiver, 
a heading-hold gyro, and other avionics command/control components. The standard off-the-shelf transmitter, included in the basic system, is used as the ground controller.
A utility patent application was submitted to the U.S. Patent Office in June 2003. The patent was granted nine months later in March 2004. The patent, the core of NRI’s intellectual property, covers the underlying techniques used to design the “intelligent” flight control software modules. This technology provides the characteristic stability, smoothness (crucial for aerial photography), and robustness.
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info@neural-robotics.com (615) 859-9882 www.neural-robotics.com |
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