Property-based Brittleness Analysis of Temporal Networks, with application to Planetary Rovers and Bio-Manufacturing

We propose a new framework to analyze the brittleness of task networks with respect to an arbitrary set P = {P1, ..., Pk} of user-specified properties, such as dynamic controllability or minimum battery state of charge of a rover. The proposed algorithms allow the detection and enumeration of activities that, with modest task execution duration variation, make the success of execution no longer guaranteed in terms of the given set of properties. We introduce a metric for measuring an activity's brittleness, defined as the degree of acceptable deviation from its nominal duration that preserve the desired user-specified properties, and describe how that measurement is mapped to task network structure. Complementary to existing work on temporal robustness analysis which informs how likely a task network is to succeed or not under temporal controllability constraints, these new analysis and metric not only generalize robustness analysis to a set of user-defined properties (as opposed to strong or dynamic controllability for instance), but it also goes deeper to pinpoint the sources of potential brittleness. We develop an analyzer that helps human designers and/or automated task network generators focus on and address sources of undesirable brittleness. We apply the approach to a set of task networks in development for NASA's Perseverance rover and present common patterns that are sources of brittleness. The proposed technique and tools are currently under evaluation for potential use supporting operations of the rover.