Towards Incremental Development of Human-Agent-Robot Applications using Mixed-Reality Testbeds

Abstract

Testing is essential part of the development of human-agent-robot team (HART) applications. Individual algorithms in such applications cannot be tested in isolation as their performance depends significantly on complex interactions among distributed software code, humans, hardware and the target environment. Any testing involving robots and human actors is, however, time-consuming and costly. We therefore propose an incremental development framework employing mixed-reality testbeds, which can reduce testing cost by replacing parts of the application and surrounding reality with synthetic computational models. The proposed framework introduces the concept of testbed fidelity and proposes how test reliability and cost should be managed to maximize the effectiveness of the development process. The framework is illustrated on two example applications in the domain of multi-UAV tracking and anti-maritime piracy operations.