Periodic Reporting for period 2 - EXTREMA (Engineering Extremely Rare Events in Astrodynamics for Deep-Space Missions in Autonomy)
Reporting period: 2022-07-01 to 2023-12-31
Solar system exploration is carried out with probes guided from ground. During their cruise toward planets, asteroids, or comets, interplanetary probes are operated by dedicated teams that reconstruct the spacecraft position and elaborate a flight plan consistent with the mission requirements. This approach requires a significant effort in terms of human resources deployed and ground-based assets used. Given the time scale of an interplanetary cruise (months or even years), the current paradigm makes it considerably costly to operate spacecraft from ground.
In the last decade, miniaturization of electronics has enabled nanosatellites, or CubeSats: shoebox-sized systems that are able to carry out scientific investigations alike conventional spacecraft. CubeSats have reduced the entry-level cost in low-Earth orbit by one order of magnitude, and are nowadays the standard for NASA, ESA, and ASI, among others. Nevertheless, the current paradigm prevents their usage for deep-space exploration: operating CubeSats might require the same costs as developing them, so canceling their advantages. This is the context in which EXTRAMA operates.
Engineering Extremely Rare Events in Astrodynamics for Deep-Space Missions in Autonomy, or EXTREMA, introduces “self-driving interplanetary CubeSats”: miniaturized probes able to drive themselves during the cruise, without requiring any contact with ground. The idea is challenging: nanosatellites must self-determine their position by sensing the environment, and must elaborate a guidance law to actuate by virtue of miniaturized thrusters. The project embeds elements of artificial intelligence and exploits ballistic capture, a delicate celestial mechanism to acquire an orbit about a planet.
This has tremendous potential. Nowadays, the outer space is a prerogative of few large agencies. Lowering the entry-level cost makes it more accessible by small institutions that cannot afford a conventional mission, which leads to more missions. And more missions mean more scientific investigation and an improved knowledge of the solar system for the benefit of the humankind.
In the last decade, miniaturization of electronics has enabled nanosatellites, or CubeSats: shoebox-sized systems that are able to carry out scientific investigations alike conventional spacecraft. CubeSats have reduced the entry-level cost in low-Earth orbit by one order of magnitude, and are nowadays the standard for NASA, ESA, and ASI, among others. Nevertheless, the current paradigm prevents their usage for deep-space exploration: operating CubeSats might require the same costs as developing them, so canceling their advantages. This is the context in which EXTRAMA operates.
Engineering Extremely Rare Events in Astrodynamics for Deep-Space Missions in Autonomy, or EXTREMA, introduces “self-driving interplanetary CubeSats”: miniaturized probes able to drive themselves during the cruise, without requiring any contact with ground. The idea is challenging: nanosatellites must self-determine their position by sensing the environment, and must elaborate a guidance law to actuate by virtue of miniaturized thrusters. The project embeds elements of artificial intelligence and exploits ballistic capture, a delicate celestial mechanism to acquire an orbit about a planet.
This has tremendous potential. Nowadays, the outer space is a prerogative of few large agencies. Lowering the entry-level cost makes it more accessible by small institutions that cannot afford a conventional mission, which leads to more missions. And more missions mean more scientific investigation and an improved knowledge of the solar system for the benefit of the humankind.
EXTREMA’s ambition is to answer the following Research Question: To what extent can we navigate the Solar System free of human supervision? In order to answer it, the project builds on three main Pillars:
- Pillar 1: Autonomous Navigation, which focuses on the development, verification, and validation of navigation algorithms to enable CubeSat to locate themselves in deep space in a completely autonomous fashion;
- Pillar 2: Autonomous Guidance and Control, which aims to develop, verify, and validate a lightweight guidance algorithm to compute a time-definite guidance profile and achieve the mission target in complete autonomy;
- Pillar 3: Ballistic Capture, where an extremely rare event in astrodynamics is synthetized aboard the spacecraft to make it possible to acquire an orbit about a planet without implementing maneuvers.
On top of the three pillars lies the EXTREMA Simulation Hub, or ESH, where the outcome of the pillars is merged to perform integrated simulations to validate the envisaged concept. The work performed is summarized here below in term of these project’s building blocks.
In Pillar 1, we have developed an autonomous navigation algorithm pipeline that ranges from the image processing to the full state estimation. The whole navigation chain has been deployed on a hardware that is representative of the computational resources available on board. In parallel, we have developed two optical facilities, TinyV3RSE and RETINA, for the validation of the autonomous navigation with hardware means.
In Pillar 2, we have developed autonomous navigation algorithms based on convex programming. These algorithms have been developed by paying particular attention to the computational burden, in order to make them not only deployable but also executable aboard. In parallel, the facility ETHILE for the verification and validation of the guidance algorithms, has been developed and assembled.
In Pillar 3, we characterized ballistic capture corridors, studying their peculiarities and understanding their potential exploitation as pathways guaranteeing temporary capture at major planets for autonomous, deep-space CubeSats. We devised an autonomous ballistic capture algorithm for the inexpensive synthesis of ballistic capture corridors. The algorithm was made compatible with limited-capability, autonomous, interplanetary CubeSats.
For what concerns the ESH, we have developed the fundamental building blocks, namely SPESI, STASIS, and the flatsat OBC. SPESI is the Space Environment Simulator, which takes care of the spacecraft-environment simulation and represents the simulation authority. STASIS is the SpacecrafT Attitude Simulation System, which is used to simulate the spacecraft attitude dynamics and control. The flatsat On-Board Computer (OBC) was developed in terms of both software and hardware; it controls the pillars experiments and represents the spacecraft authority.
- Pillar 1: Autonomous Navigation, which focuses on the development, verification, and validation of navigation algorithms to enable CubeSat to locate themselves in deep space in a completely autonomous fashion;
- Pillar 2: Autonomous Guidance and Control, which aims to develop, verify, and validate a lightweight guidance algorithm to compute a time-definite guidance profile and achieve the mission target in complete autonomy;
- Pillar 3: Ballistic Capture, where an extremely rare event in astrodynamics is synthetized aboard the spacecraft to make it possible to acquire an orbit about a planet without implementing maneuvers.
On top of the three pillars lies the EXTREMA Simulation Hub, or ESH, where the outcome of the pillars is merged to perform integrated simulations to validate the envisaged concept. The work performed is summarized here below in term of these project’s building blocks.
In Pillar 1, we have developed an autonomous navigation algorithm pipeline that ranges from the image processing to the full state estimation. The whole navigation chain has been deployed on a hardware that is representative of the computational resources available on board. In parallel, we have developed two optical facilities, TinyV3RSE and RETINA, for the validation of the autonomous navigation with hardware means.
In Pillar 2, we have developed autonomous navigation algorithms based on convex programming. These algorithms have been developed by paying particular attention to the computational burden, in order to make them not only deployable but also executable aboard. In parallel, the facility ETHILE for the verification and validation of the guidance algorithms, has been developed and assembled.
In Pillar 3, we characterized ballistic capture corridors, studying their peculiarities and understanding their potential exploitation as pathways guaranteeing temporary capture at major planets for autonomous, deep-space CubeSats. We devised an autonomous ballistic capture algorithm for the inexpensive synthesis of ballistic capture corridors. The algorithm was made compatible with limited-capability, autonomous, interplanetary CubeSats.
For what concerns the ESH, we have developed the fundamental building blocks, namely SPESI, STASIS, and the flatsat OBC. SPESI is the Space Environment Simulator, which takes care of the spacecraft-environment simulation and represents the simulation authority. STASIS is the SpacecrafT Attitude Simulation System, which is used to simulate the spacecraft attitude dynamics and control. The flatsat On-Board Computer (OBC) was developed in terms of both software and hardware; it controls the pillars experiments and represents the spacecraft authority.
In the autonomous navigation pillar, we have shown that the celestial triangulation is a viable option to navigate deep-space probes without human intervention. In particular, under certain condition, the target accuracy of 1000 km error on position estimation has been met with processor-in-the-loop simulations, which account for the computational resources available aboard miniaturized probes.
In the autonomous guidance pillar, we have developed novel algorithms based on convex programming. These algorithms have been deployed on in-flight representative hardware, and a simulation campaign with a processor-in-the-loop approach has been performed in this pillar as well. The initial results confirm the suitability of these algorithms for self-driving spacecraft, which was an open point. The target of reaching a moving body has been achieved.
As part of the autonomous ballistic capture algorithm, we devised a methodology for the generation of ballistic capture orbit families, inferring dynamical information by extracting from the dynamics what we called the backbone of the ballistic capture set, and cheaply synthesizing corridors directly on-board the spacecraft. Next, we expect to deploy the autonomous ballistic capture algorithm on relevant equipment to verify and validate its effectiveness when tested in hardware-in-the-loop experiments.
In the autonomous guidance pillar, we have developed novel algorithms based on convex programming. These algorithms have been deployed on in-flight representative hardware, and a simulation campaign with a processor-in-the-loop approach has been performed in this pillar as well. The initial results confirm the suitability of these algorithms for self-driving spacecraft, which was an open point. The target of reaching a moving body has been achieved.
As part of the autonomous ballistic capture algorithm, we devised a methodology for the generation of ballistic capture orbit families, inferring dynamical information by extracting from the dynamics what we called the backbone of the ballistic capture set, and cheaply synthesizing corridors directly on-board the spacecraft. Next, we expect to deploy the autonomous ballistic capture algorithm on relevant equipment to verify and validate its effectiveness when tested in hardware-in-the-loop experiments.