Selecting Minimal Motion Primitive Libraries with Genetic Algorithms

Journal Article · 29 July 2023 · Journal of Aerospace Information Systems

DOI: https://doi.org/10.2514/1.i011188 · OSTI ID:2311494

Goddard, Zachary C.  ^[1]; Wardlaw, Kenneth  ^[1]; Williams, Kyle  ^[2]; Mazumdar, Anirban  ^[1]

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1. Georgia Institute of Technology, Atlanta, GA (United States)
2. Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Pathfinder Technologies, Inc., Cerritos, CA (United States)

Motion primitives allow for application of discrete search algorithms to rapidly produce trajectories in complex continuous space. The maneuver automaton (MA) provides an elegant formulation for creating a primitive library based on trims and maneuvers. However, performance is fundamentally limited by the contents of the primitive library. If the library is too sparse, performance can be poor in terms of path cost, whereas a library that is too large can increase run time. This work outlines new methods for using genetic algorithms to prune a primitive library. The proposed methods balance the path cost and planning time while maintaining the reachability of the MA. The genetic algorithm in this paper evaluates and mutates populations of motion primitive libraries to optimize both objectives. Here, we illustrate the performance of these methods with a simulated study using a nonlinear medium-fidelity F-16 model. We optimize a library with the presented algorithm for obstacle-free navigation and a nap-of-the-Earth navigation task. In the obstacle-free navigation task, we show a tradeoff of a 10.16% higher planning cost for a 96.63% improvement in run time. In the nap-of-the-Earth task, we show a tradeoff of a 9.712% higher planning cost for a 92.06% improvement in run time.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: NA0003525
• OSTI ID: 2311494
• Report Number(s): SAND--2024-00369J
• Journal Information: Journal of Aerospace Information Systems, Journal Name: Journal of Aerospace Information Systems Journal Issue: 10 Vol. 20; ISSN 1940-3151
• Publisher: American Institute of Aeronautics and AstronauticsCopyright Statement
• Country of Publication: United States
• Language: English