Alex Fraley · Test engineering

Aerospace and robotics test engineering.

For five years at the NIST Engineering Laboratory, I developed and ran test methods for the robots and small uncrewed aircraft used in emergency response: the procedures, the field apparatus, the experimental computer-vision scoring software, and the field trials themselves.

I now apply the same discipline to software, data, and AI systems. The core of the work has not changed: exercise a system carefully toward the edge of its operating envelope, establish where its behavior changes, and report what an operator can depend on.

Overview

Three ways into the work.

One career, three views: the full NIST chapter, the individual engineering stories, or the whole sequence on a single line.

Career chapter

The NIST years

Five years of field test methods, robots, drones, standards contributions, and a published wildfire paper, told as one connected chapter.

Read the chapter
For the 2024 RoboCup championship, the arena terrain was modeled in CAD, including a metric 3D floorplan, so the next venue could rebuild it exactly. More than one hundred quadruped mobility trials ran on terrain like that.
Field note · RoboCupRescue · ICRA · IROS
Event terrainIllustrative schematic
Mobility terrain of the kind used in event arenas. Schematic, not a specific arena drawing.
UAS field operations
Test apparatus
Event trials
Independent engineering · Curiosell Systems

Current technical work.

Independent engineering under Curiosell Systems, spanning release engineering, robotics software, procedural simulation environments, computer vision, and edge and embedded systems.

  • CURIRelease engineering with deterministic builds, release verification, installed-state verification, and reversible deployment with rollback and uninstall.
  • DRONIEUSProcedural drone-simulation environments and infrastructure tooling, with Unreal-ready scene workflows and experimental Unreal Engine 5.7 simulator work.
  • JetBot ControlRobot-control software for JetBot platforms: an iOS MVP validated on device, with Android work in progress.
  • Edge and embeddedJetson and ESP32-class prototyping: edge computer vision, telemetry, and local automation.

If you have a system whose real capability needs to be established, I would like to hear about it.