Marc Takahashi

A system for 3D autonomous rotorcraft navigation in urban environments

Three-dimensional navigation will be an essential component of low-altitude unmanned rotorcraft operations in urban environments. Successful navigation will require that the vehicle sense the surrounding obstacles, incorporate the data into its world model, and react to new obstacles to ensure both vehicle survivability and satisfactory completion of the mission objectives. A complete navigation solution built on heuristic planning concepts is presented. A fast A*-based 3D route planner is compared with one that constructs 3D routes by executing a 2D planner on plane slices of the terrain. Monte Carlo simulation evaluation and flight test validation results are presented.

Autonomous Black Hawk in Flight: Obstacle Field Navigation and Landing-site Selection on the RASCAL JUH-60A

This paper describes the development and flight test of autonomous obstacle field navigation and safe landing area selection on the U.S. Army Aeroflightdynamics Directorate RASCAL JUH-60A research helicopter. Using laser detection and ranging LADAR as the primary terrain sensor, the autonomous flight system is able to avoid obstacles, including wires, and select safe landing sites. An autonomous integrated landing zone approach profile was developed and validated that integrates cruise flight, low-level terrain flight, and approach to a safe landing spot determined on the fly. Results are presented for a range of sites and conditions. Approximately 750i¾?km of autonomous flight was performed, 230i¾?km of which was at low altitude in mountainous terrain using the obstacle field navigation system. This is the first time a full-scale helicopter has been flown fully autonomously a significant distance in low-level flight over complex terrain, basing its planning solely on sensor data gathered from an onboard sensor. These flights demonstrate tight integration between terrain avoidance, control, and autonomous landing.