Paper
5 May 2017 A systematic approach to autonomous unmanned system experimentation
Ryan Halterman, Chris Scrapper
Author Affiliations +
Abstract
Regimented experimentation of autonomous unmanned vehicles is an important enabler for performance assessment, issue identification, and root-cause analysis. As autonomous capabilities improve, these are increasingly problems of needles and haystacks; large amounts of test data are often required to fully identify and analyze erratic events. Acquisition and analysis of this test data can be arduous, error prone, and inefficient.

Driven by a philosophy that test methods should be repeatable, reproducible, and as automated as possible, we have developed an experimentation regime for expeditionary autonomous unmanned vehicles. This regime represents a method of decomposing functionality, building up evidentiary information, and analyzing component results on overall system performance despite the challenge of testing to sufficient statistical significance. We have also developed a set of methods and tools that automate data collection and analysis to facilitate experimentation. This paper describes this test and experimentation philosophy, regime, and associated tools developed under the Office of Naval Research, Code 30 Ground Vehicle Autonomy program.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ryan Halterman and Chris Scrapper "A systematic approach to autonomous unmanned system experimentation", Proc. SPIE 10195, Unmanned Systems Technology XIX, 101950M (5 May 2017); https://doi.org/10.1117/12.2266798
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KEYWORDS
Error analysis

Calibration

Data modeling

Sensors

Image segmentation

Velocity measurements

Cameras

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