Modelbased testing of autonomous robots using TestIt This paper presents a testing toolkit named TestIt. Its main goal is to provide tools for automated modelbased testing of autonomous multirobot systems to verify longterm autonomy in various applications including those of smart city environments and smart buildings. The main novelty of the presented toolkit is the open and scalable multipipeline architecture that enables incorporation of test development and execution tools from various vendors. The second main contribution is adaptive test optimization technique that takes advantage of the proposed multipipeline architecture where testing threads can communicate and coordinate the test runs based on their cooperatively collected test performance data. The usability of TestIt for test generation, testing process performance improvement and optimization in multirobot autonomous navigation context is demonstrated using a smart building robotic security system case study.

SimulationBased Testing to Improve Safety of Autonomous Robots Autonomous systems are becoming increasingly popular among industries as well as endusers, and are deployed in numerous tasks. To improve their reliability and to avoid critical failures that impact safety, their testing aims at ensuring that their behavior and decisions are acceptable even in scenarios that have not been foreseen by the developers. As testing of these systems is usually done through field testing, which is costly and is limited in the reproducible scenarios, systemlevel prevalidation can be done in virtual worlds through simulation, to discover faults and fix them before deploying the system in the real world. However, there is no current standard procedure to conduct simulationbased testing and to ensure satisfying coverage of the most critical scenarios for the system under test (SUT). The aim of this experimental work is to improve and automate the steps of the simulationbased testing related to the generation and selection of test inputs, the exploitation of the results, and the incorporation of dynamic agents in the tests.