Evaluation of Three Sequence Engines for Use in Spacecraft Operations

As NASA and commercial space missions venture further out into the solar system, there will be an increasing need for autonomous and/or semi-autonomous agents to perform a variety of basic and advanced sequential tasks to allow the crew to not only focus on more essential human-operated tasks, such as performing scientific research, but also reduce the risks to human life in deep space exploration. A key component of these autonomous agents will be the usage of one or more sequence engines which will be capable of performing various automated scripted sequences for a variety of tasks. Autonomous sequence engines are currently being used on the International Space Station (ISS) through the use of high-level sequence engines, which allow the astronauts to control autonomous tasks more easily through readable commands. These sequence engines are essential for autonomous systems as they are capable of performing many of the routine and repetitive tasks that are currently completed by crew members.There are currently three candidate sequence engines that could be used for deep space autonomous operations. This proposal seeks to perform a detailed analysis and evaluation of the capabilities of three existing autonomous software sequence engines that are currently being utilized in the space industry: Plan Execution Interchange Language (PLEXIL), Virtual Machine Language (VML) 3.0, and Timeliner. This evaluation will focus on the responsiveness, performance, and usefulness of these sequence engines in a variety of scenarios including the frequent, repetitive tasks typically conducted by astronauts. Additionally, this study will evaluate the ease of use and functionality of the sequence engines for the Fault Detection, Identification, and Recovery (FDIR) of potential failure modes onboard spacecraft or more permanent space habitats.