The ISC is part of the Johns Hopkins Applied Physics Laboratory and will follow all current policies. Please visit the JHU/APL page for more information on the Lab's visitor guidance.


APL Researchers Know the CODE to Unmanned Aircraft Program’s Success

Read full story
Article Keywords
Trustworthy Systems
Autonomous Systems

A multidisciplinary team of researchers from the Johns Hopkins University Applied Physics Laboratory (APL) in Laurel, Maryland, is helping to solve one of the Defense Department’s most significant challenges: the test and evaluation of autonomous unmanned aerial systems.


DoD has recently expanded the roles and capabilities of unmanned systems in keeping with its desire to use autonomy to improve performance — through increased operational speed, reduced cognitive load and increased performance in denied environments. The test, evaluation, verification and validation of these systems is a critical element in building the high assurance of autonomy.


APL has developed the White Force Network (WFN), a highly sophisticated test infrastructure that injects key capabilities — such as communications and navigation in areas without GPS access — virtually into flying unmanned systems. “It also features a test director’s workstation that displays data for all of the test assets and software switches to implement the denial services,” said Reed Young, program manager for robotics and autonomy in APL’s Research and Exploratory Development Department.


WFN was originally designed as an extension of the live, virtual and constructive (LVC) simulation infrastructure developed for DoD’s Safe Testing of Autonomy in Complex Interactive Environments (TACE) program, which provided a baseline of LVC capabilities. TACE was funded by the Test Resource Management Center, the Test Evaluation/Science & Technology Program and the U.S. Army Contracting Command Orlando.


Through these extensions, WFN can create synthetic entities that team seamlessly with CODE-enabled vehicles to execute defined missions. In addition, WFN can simulate an opposing force of moving targets and various threats to stimulate defined autonomous behaviors and determine the overall performance of the unmanned aircraft team.