A Comparison of Automatic Nap-of-the-earth Guidance Strategies for Helicopters

This paper describes updated results from a partnership between the Sikorsky Aircraft Corporation and the Georgia Institute of Technology to develop, improve, and flight test a sensor, guidance, navigation, control, and real-time flight path optimization system to support high performance Nap-of-the-Earth (NOE) helicopter flight. The emphasis here is on optimization for a combination of low height above terrain/obstacles and high speeds. Here, multiple obstacle mapping and guidance methods for generating the desired flight path are evaluated, including (1) a simple processing of each laser scan; (2) a motion primitive optimization method, and (3) a potential field based method. Simulation and flight test results have been obtained utilizing an onboard laser scanner to detect terrain and obstacles while flying at low altitude, and have successfully demonstrated obstacle avoidance in a realistic semi-urban environment at speeds up to 15 m/s while maintaining a miss distance of 15 m horizontally and vertically. Additionally, the performance of the selected LADAR model in multiple degraded environments was observed. The performance of the three guidance methods are compared to a published benchmark model. These results validate the above approaches and pave the way for extensions to this work, including multi-aircraft collaboration and other more complex scenarios.