3.0RONov 22, 2021
Operations for Autonomous SpacecraftRebecca Castano, Tiago Vaquero, Federico Rossi et al.
Onboard autonomy technologies such as planning and scheduling, identification of scientific targets, and content-based data summarization, will lead to exciting new space science missions. However, the challenge of operating missions with such onboard autonomous capabilities has not been studied to a level of detail sufficient for consideration in mission concepts. These autonomy capabilities will require changes to current operations processes, practices, and tools. We have developed a case study to assess the changes needed to enable operators and scientists to operate an autonomous spacecraft by facilitating a common model between the ground personnel and the onboard algorithms. We assess the new operations tools and workflows necessary to enable operators and scientists to convey their desired intent to the spacecraft, and to be able to reconstruct and explain the decisions made onboard and the state of the spacecraft. Mock-ups of these tools were used in a user study to understand the effectiveness of the processes and tools in enabling a shared framework of understanding, and in the ability of the operators and scientists to effectively achieve mission science objectives.
3.3IMSep 15, 2020
Advancing the Scientific Frontier with Increasingly Autonomous SystemsRashied Amini, Abigail Azari, Shyam Bhaskaran et al.
A close partnership between people and partially autonomous machines has enabled decades of space exploration. But to further expand our horizons, our systems must become more capable. Increasing the nature and degree of autonomy - allowing our systems to make and act on their own decisions as directed by mission teams - enables new science capabilities and enhances science return. The 2011 Planetary Science Decadal Survey (PSDS) and on-going pre-Decadal mission studies have identified increased autonomy as a core technology required for future missions. However, even as scientific discovery has necessitated the development of autonomous systems and past flight demonstrations have been successful, institutional barriers have limited its maturation and infusion on existing planetary missions. Consequently, the authors and endorsers of this paper recommend that new programmatic pathways be developed to infuse autonomy, infrastructure for support autonomous systems be invested in, new practices be adopted, and the cost-saving value of autonomy for operations be studied.
6.6IMJul 29, 2020
Integrating Machine Learning for Planetary Science: Perspectives for the Next DecadeAbigail R. Azari, John B. Biersteker, Ryan M. Dewey et al.
Machine learning (ML) methods can expand our ability to construct, and draw insight from large datasets. Despite the increasing volume of planetary observations, our field has seen few applications of ML in comparison to other sciences. To support these methods, we propose ten recommendations for bolstering a data-rich future in planetary science.
7.0ROMar 16, 2020
The Shapeshifter: a Morphing, Multi-Agent,Multi-Modal Robotic Platform for the Exploration of Titan (preprint version)Ali-akbar Agha-mohammadi, Andrea Tagliabue, Stephanie Schneider et al.
In this report for the Nasa NIAC Phase I study, we present a mission architecture and a robotic platform, the Shapeshifter, that allow multi-domain and redundant mobility on Saturn's moon Titan, and potentially other bodies with atmospheres. The Shapeshifter is a collection of simple and affordable robotic units, called Cobots, comparable to personal palm-size quadcopters. By attaching and detaching with each other, multiple Cobots can shape-shift into novel structures, capable of (a) rolling on the surface, to increase the traverse range, (b) flying in a flight array formation, and (c) swimming on or under liquid. A ground station complements the robotic platform, hosting science instrumentation and providing power to recharge the batteries of the Cobots. Our Phase I study had the objective of providing an initial assessment of the feasibility of the proposed robotic platform architecture, and in particular (a) to characterize the expected science return of a mission to the Sotra-Patera region on Titan; (b) to verify the mechanical and algorithmic feasibility of building a multi-agent platform capable of flying, docking, rolling and un-docking; (c) to evaluate the increased range and efficiency of rolling on Titan w.r.t to flying; (d) to define a case-study of a mission for the exploration of the cryovolcano Sotra-Patera on Titan, whose expected variety of geological features challenges conventional mobility platforms.