2019.A.1.3. DLR developments and application ideas for interplanetary cubesats

Author(s)

Jens Biele (1)
Caroline Lange (2)
Thimo Grundmann (2)
Stephan Ulamec (1)
Marcus Thomas Knopp (3)
Frank-Cyrus Roshani (3)

DLR RB-MUSC, Cologne, Germany
DLR RY, Bremen, Germany
DLR German Aerospace Center, GSOC, Munich, Germany

Session

A.1

Keywords

deployable payloads, distributed systems, small body landers

Abstract

While numerous cubesats have been launched into Earth orbit, the initial designs of this new class of spacecraft for scientific use had to fight an uphill battle against the numerous very capable large satellites in orbit providing services that are well established or packaged in ways customers are already used to. However, there have been science missions which were critically enabled by the small size of nanosatellites or the option to deploy many at a time, e.g. QB50. The use of cubesats for the exploration of the Solar System is still in its infancy. Interplanetary cubesats, if well designed, can become dependable assets, as has been recently demonstrated by JPL with MARCO for InSight.

DLR developed the nano-lander MASCOT, which operated on asteroid Ryugu in 2018. Customized nanospacecraft like the asteroid landers MINERVA-II and MASCOT aboard JAXA’s Hayabusa2 mission have proven themselves in critical risk-taking scouting missions for their larger mothership. Small spacecraft missions are indeed “the new frontier”, they provide as well as call for innovative solutions which induce new concepts, technologies, and development approaches that are ‘non-standard’ in the established space research and industrial environment.

The proposed ESA Hera Mission to Didymos is planned to accommodate two cubesats, APEX and Juventus, to be deployed in the Didymos system.

Here, we survey the general possibilities for utilization of cubesats complementing conventional interplanetary probes to enhance the scientific outcome of the mission. Putting focus on deployable payloads, distributed systems and small body landers, we find a huge potential to mitigate risks and obtain very interesting data at low cost.