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The Curiosity rover is one of the most complex systems successfully deployed in a planetary exploration mission to date. It was sent by NASA to explore the surface of Mars and to identify potential signs of life. Even though it has limited autonomy on-board, most of its decisions are made by the ground control team. This hinders the speed at which the Curiosity reacts to its environment, due to the communication delays between Earth and Mars. Depending on the orbital position of both planets, it can take 4--24 minutes for a message to be transmitted between Earth and Mars. If the Curiosity were controlled autonomously, it would be able to perform its activities much faster and more flexibly. However, one of the major barriers to increased use of autonomy in such scenarios is the lack of assurances that the autonomous behaviour will work as expected. In this paper, we use a Robot Operating System (ROS) model of the Curiosity that is simulated in Gazebo and add an autonomous agent that is responsible for high-level decision-making. Then, we use a mixture of formal and non-formal techniques to verify the distinct system components (ROS nodes). This use of heterogeneous verification techniques is essential to provide guarantees about the nodes at different abstraction levels, and allows us to bring together relevant verification evidence to provide overall assurance.
Ensuring that autonomous space robot control software behaves as it should is crucial, particularly as software failure in space often equates to mission failure and could potentially endanger nearby astronauts and costly equipment. To minimise missi
Sample-efficient exploration is crucial not only for discovering rewarding experiences but also for adapting to environment changes in a task-agnostic fashion. A principled treatment of the problem of optimal input synthesis for system identification
The battery is a key component of autonomous robots. Its performance limits the robots safety and reliability. Unlike liquid-fuel, a battery, as a chemical device, exhibits complicated features, including (i) capacity fade over successive recharges a
Terrain assessment is a key aspect for autonomous exploration rovers, surrounding environment recognition is required for multiple purposes, such as optimal trajectory planning and autonomous target identification. In this work we present a technique
Web testing has long been recognized as a notoriously difficult task. Even nowadays, web testing still heavily relies on manual efforts while automated web testing is far from achieving human-level performance. Key challenges in web testing include d