Fast, Robust Real-Time Trajectory Generation for Autonomous and Semi-Autonomous Nonlinear Flight Systems

Period of Performance: 08/16/2002 - 08/16/2003

$99.9K

Phase 1 STTR

Recipient Firm

Information Systems Laboratories, Inc.
10070 Barnes Canyon Road Array
San Diego, CA 92121
Principal Investigator
Firm POC

Research Institution

Brigham Young University
A-285 ASB
Provo, UT 84602
Institution POC

Abstract

Our approach is to decompose the trajectory generation problem into three distinct, but tightly coupled pieces: waypoint path planning (WPP), dynamic trajectory smoothing (DTS), and adaptive trajectory tracking (ATT). The WPP plans paths at a high level without regard for the dynamic constraints of the vehicle. This affords a significant reduction in the search space, enabling the generation of extremely complicated paths that account for pop-up threats and dynamically changing threats. The essential idea of the DTS is to give the trajectory generator a similar mathematical structure as the physical vehicle. The DTS uses a simple, but novel algorithm to generate smoothed trajectories in real-time without performing any on-line optimization. The trajectories that are generated by the DTS have the same path length as the waypoint path generated by the WPP and also minimize the deviation from the waypoint path. The third step of our approach uses adaptive backstepping to transform the trajectory generated by the DTS to a feasible trajectory that can be followed by an autopilot with appropriate velocity, altitude and heading commands. The proposed approach is computationally efficient: it can handle hundreds of threats, including pop-up threats. It does not require on-line optimization. Is very well suited to applications with timing constraints. Planning can take place at the waypoint level, where it is trivial to calculate path length, and therefore estimated time-of-arrival (ETA). The trajectories can be represented in a compact fashion, in both space and time. In particular, this will allow higher-level task planning algorithms to reason about the feasibility, or desirability of different trajectories.