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 helicopter flight. Multiple obstacle avoidance methods 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 they have successfully demonstrated obstacle avoidance in a realistic semiurban environment at speeds up to 12 m/s while maintaining a specified vertical and horizontal miss distance. Additionally, the performance of the selected LIDAR model in multiple degraded environments was observed. The performances of the three guidance methods are directly compared, using a published benchmark performance for reference. These results validate the above approaches and pave the way for extensions to this work, including investigation of additional motion primitives and the relationship between sensor range and aircraft performance requirements.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Science Applications