Automated Verification and Validation of an Onboard Mission Planning and Execution System for UAVs

Abstract

Automated mission planning is one of the key components of an autonomous UAV. The software validation and verification for such decisional autonomy functions is a challenging problem. The software component includes the closed loop vehicle control as well as environment perception. As this is a safety-critical software component, it is important that this software works safely and within projected performance boundaries. This paper discusses the verification and validation approach for the sampling-based mission planner of an unmanned rotorcraft. A layered test strategy is presented, which utilizes different testing methods that complement and build upon each other. Its strengths as well as the possible improvement directions of this approach are discussed. An emphasis is given on automated software-in-the-loop simulations. The approach additionally utilizes benchmarks to assess the implementation performance and real time properties. Finally, to be able to assess the overall test quality, a set of different scalable test abstractions (SUT size, test effort, level of automation, coverage, test complexity and feedback time) is used to analyze the presented strategy.