Planning Flight Paths of Autonomous Aerobots

Trajectories are planned to satisfy survey coverage requirements without violating dynamical constraints.

Algorithms for planning flight paths of autonomous aerobots (robotic blimps) to be deployed in scientific exploration of remote planets are undergoing development. These algorithms are also adaptable to terrestrial applications involving robotic submarines as well as aerobots and other autonomous aircraft used to acquire scientific data or to perform surveying or monitoring functions.

This Raster-Scan Trajectory was calculated to enable surveying, from a fixed altitude, of a defined rectangular area by use of a camera having a rectangular field of view. First, the survey area was mapped using successive fields of view that were required to overlap by 35 percent in length and/or width. Then the centers of the successive fields of view were designated as waypoints. Finally, the waypoints were used to generate the trajectory.
These algorithms are built on a number of previously developed algorithms for planning optimal trajectories in two- and three-dimensional spaces. As used here, “optimal” could have any of a variety of different meanings. For example, “optimal” could be used to characterize a trajectory that passes through a set of waypoints specified by a user and that satisfies a minimum-length or a minimum-time criterion while also remaining within limits posed by dynamical and resource constraints. The present algorithms can also satisfy a requirement that the trajectory suffice to enable the field of view of camera aboard an aerobot to sweep all of a specified ground area to be surveyed (see figure).

A navigation software system that implements these algorithms generates a simple graphical user interface, through which the user can specify either waypoints in two or three dimensions or the ground area to be surveyed. Alternatively, the user can load a data file containing waypoint coordinates. The user can also specify other parameters that affect the planned trajectory, including the field of view of the camera and the dynamical parameters, the primary one being the minimum allowable turn radius of the aerobot. Then assuming constant airspeed, the algorithms compute a minimum-time or minimum-length trajectory that takes account of all of the aforementioned requirements and constraints. Notably, in one of the algorithms, the turning dynamics of the aerobot are represented by a cubic spline that is used to interpolate the trajectory between waypoints.

In some contemplated future versions, the need for intervention by human users would be reduced: Waypoints specified by users could be supplanted by data generated by onboard artificial-intelligence image-data-processing systems programmed to strive to satisfy mission specifications.

This work was done by Eric Kulczycki and Alberto Elfes of Caltech and Shivanjli Sharma of University of California at Davis for NASA’s Jet Propulsion Laboratory.

The software used in this innovation is available for commercial licensing. Please contact Karina Edmonds of the California Institute of Technology at (626) 395-2322. Refer to NPO-44395.

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