Operating Deep Space Autonomous Spacecraft: Ground Processes and Tools for Operability and Trust

Future deep-space robotic explorers will use advanced onboard autonomy to address high-priority science questions, e.g., observing fast-changing phenomena and adapting to dynamic environmental circumstances. Onboard autonomy technologies such as planning and scheduling, identification of scientific targets, and content-based data summarization will lead to exciting new deep space science missions. However, traditional operations practices, skills, and processes were not designed for spacecraft with such onboard autonomous capabilities. This paper summarizes the results of a two-year investigation conducted at JPL to explore how ground operations processes, practices, and tools will need to adapt to support effective use of onboard autonomy. In particular, we identify areas where current workflows and tools will need to be enhanced to accommodate commanding and analysis onboard planning and scheduling software for deep space exploration. Our focus is on onboard planning and scheduling: we identify the required changes necessary to enable operators and scientists to convey their desired intent to future autonomous spacecraft’s planning and execution systems, and to be able to reconstruct and explain the decisions made onboard and the state of the spacecraft - providing a practical path to users trusting the autonomy, which is one of the most significant barriers to full adoption. Collectively, these results form key steps toward adoption of onboard spacecraft autonomy, which will enable new, bolder exploration of the outer solar system, small bodies, and the surface of ocean worlds.