Robust Model-based Execution of Critical Spacecraft Sequences

Abstract

For robotic spacecraft, robust plan execution is essential during time-critical mission sequences, due to the very short time available for recovery from anomalies. Traditional approaches to encoding these sequences can lead to brittle behavior under off-nominal execution conditions, due to the high level of complexity in the control specification required to manage the complex spacecraft system interactions. This paper describes timed model-based programming, a novel approach for encoding and robustly executing mission-critical spacecraft sequences. Time is central to the execution of mission-critical sequences; a robust executive must consider time in its control and behavior models, in addition to reactively managing complexity. In timed model-based programming, control programs express goals and constraints in terms of both system state and time. Plant models capture the underlying behavior of the system components, including nominal and off-nominal modes, probabilistic transitions, and timed effects such as state transition latency. In this paper, the execution semantics of a timed model-based program are defined in terms of legal state evolutions of a physical plant, represented as a factored Partially Observable Semi-Markov Decision Process. The paper also includes the definition of graphical languages for encoding timed control programs and plant models. It describes the design of a Timed Model-based Execution architecture, which takes as input a timed control program and executes it, using timed plant models to track states, diagnose faults and generate control actions. Finally, it illustrates the execution of a timed model-based program on a simple Mars entry scenario.