Development of a Finite State Machine for a Small Unmanned Aircraft System Using Experimental Design
AIR FORCE INSTITUTE OF TECHNOLOGY WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT
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This research presents a methodology for improving the capability of a small unmanned aircraft system SUAS to autonomously track a moving ground vehicle. One drawback of the most common open source SUAS autopilot software, APMPlane, is the inability to maintain a consistent following distance from the target vehicle under varying conditions defined by wind direction, wind speed, and target vehicle maneuver. Finite state machine FSM logic was developed to improve the APMPlane software by reducing the variability in the following distance between the SUAS and the target vehicle. The FSM consists of 36 individual states defined by a combination of four wind directions, three wind speeds, and three ground maneuvers. Once the SUAS enters a particular state, the FSM modifies the default APMPlane firmware parameter settings to optimal settings. The parameter settings for each state were determined from the statistical analysis of a sequence of designed experiments conducted in a simulated environment. During a real-world software validation experiment, the FSM reduced following distance variance by an average of 50 percent when compared to the default software settings.
- Pilotless Aircraft
- Active and Passive Radar Detection and Equipment
- Target Direction, Range and Position Finding