DCFH—A JAUS and TENA Compliant Agent-Based Framework for Test and Evaluation of Unmanned Vehicles

Real-world applications for unmanned and autonomous systems (UAS) teams continue to grow, and the scale and complexity of the teams are continually increasing. To reduce life cycle costs and improve test and evaluation (T&E), we increasingly need to develop a generalized framework that can support the design and development of T&E approaches for multi-UAS teams and validate the feasibility of the concepts, architectures, and algorithms. This challenge is most significant in the cognitive–social domains, where the development of test approaches and methodologies are difficult because of the emergent nature of behaviors in response to dynamic changes in the battlespace. Today much of the initial validation effort is done using simulations, which unfortunately rarely capture the complexity of real world effects related to net-centric communications, vehicle dynamics, distributed sensors, physical environment (terrain), external disturbances, etc. Furthermore, very often high fidelity simulations do not scale because the number of UAS increases. This article addresses DCFH—a JAUS and TENA compliant agentbased T&E framework for simulated, mixed-model (virtual and live–hardware in the loop) and live testing of teams of unmanned autonomous systems.