Extended Mission Technology Demonstrations Using the ASTERIA Spacecraft

Fesq, Lorraine; Beauchamp, P.; Donner, Amanda; Bocchino, Rob; Kennedy, Brian; Mirza, Faiz; Mohan, Swati; Sternberg, David; Smith, Matthew W.; Troesch, Martina; Knapp, Mary

doi:10.1109/aero.2019.8742020

Cited by 18 publications

(8 citation statements)

References 6 publications

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“…The IPEX mission used autonomous image acquisition and data processing for downlink [48]. Most recently, the ASTERIA spacecraft transitioned its commanding from time-based sequences to task networks and demonstrated onboard orbit determination using passive imaging in Low Earth Orbit (LEO) without GPS [49].…”

Section: In-space Robotic Operationsmentioning

confidence: 99%

Autonomy for Space Robots: Past, Present, and Future

Nesnas

Fesq²,

Volpe³

2021

Curr Robot Rep

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Purpose of Review The purpose of this review is to highlight space autonomy advances across mission phases, capture the anticipated need for autonomy and associated rationale, assess state of the practice, and share thoughts for future advancements that could lead to a new frontier in space exploration. Recent Findings Over the past two decades, several autonomous functions and system-level capabilities have been demonstrated and used in spacecraft operations. In spite of that, spacecraft today remain largely reliant on ground in the loop to assess situations and plan next actions, using pre-scripted command sequences. Advances have been made across mission phases including spacecraft navigation; proximity operations; entry, descent, and landing; surface mobility and manipulation; and data handling. But past successful practices may not be sustainable for future exploration. The ability of ground operators to predict the outcome of their plans seriously diminishes when platforms physically interact with planetary bodies, as has been experienced in two decades of Mars surface operations. This results from uncertainties that arise due to limited knowledge, complex physical interaction with the environment, and limitations of associated models. Summary Robotics and autonomy are synergistic, wherein robotics provides flexibility, autonomy exercises it to more effectively and robustly explore unknown worlds. Such capabilities can be substantially advanced by leveraging the rapid growth in SmallSats, the relative accessibility of near-Earth objects, and the recent increase in launch opportunities.

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Section: In-space Robotic Operationsmentioning

confidence: 99%

Autonomy for Space Robots: Past, Present, and Future

Nesnas

Fesq²,

Volpe³

2021

Curr Robot Rep

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“…Although not the purpose of the mission, it was the first to show that a kinetic impactor could be used to deflect a potentially hazardous asteroid from hitting the Earth using the same technology. Most recently, the ASTERIA spacecraft transitioned its commanding from time-based sequences to task networks and demonstrated onboard orbit determination in low Earth orbit (LEO) without GPS, using passive imaging for orbit determination ( Fesq et al, 2019 ).…”

Section: Related Workmentioning

confidence: 99%

“…Such capabilities include perception, feature tracking for motion estimation, 3D mapping, hazard assessment, motion planning, and six-DOF control. These autonomy-enabling functions require a system-level executive ( Grasso, 2002 ; Verma et al, 2006 ; Fesq et al, 2019 ) to orchestrate these functions with the planning, execution, system health management, and data management, as was demonstrated in prior studies involving landings on the Moon and on small bodies ( Riedel et al, 2008 ; Riedel et al, 2010 ), and for understanding fundamental trade-offs concerning small-body touch-and-go sampling ( Cangahuala et al, 2011 ).…”

Section: Related Workmentioning

confidence: 99%

Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions

et al. 2021

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Autonomy is becoming increasingly important for the robotic exploration of unpredictable environments. One such example is the approach, proximity operation, and surface exploration of small bodies. In this article, we present an overview of an estimation framework to approach and land on small bodies as a key functional capability for an autonomous small-body explorer. We use a multi-phase perception/estimation pipeline with interconnected and overlapping measurements and algorithms to characterize and reach the body, from millions of kilometers down to its surface. We consider a notional spacecraft design that operates across all phases from approach to landing and to maneuvering on the surface of the microgravity body. This SmallSat design makes accommodations to simplify autonomous surface operations. The estimation pipeline combines state-of-the-art techniques with new approaches to estimating the target’s unknown properties across all phases. Centroid and light-curve algorithms estimate the body–spacecraft relative trajectory and rotation, respectively, using a priori knowledge of the initial relative orbit. A new shape-from-silhouette algorithm estimates the pole (i.e., rotation axis) and the initial visual hull that seeds subsequent feature tracking as the body gets more resolved in the narrow field-of-view imager. Feature tracking refines the pole orientation and shape of the body for estimating initial gravity to enable safe close approach. A coarse-shape reconstruction algorithm is used to identify initial landable regions whose hazardous nature would subsequently be assessed by dense 3D reconstruction. Slope stability, thermal, occlusion, and terra-mechanical hazards would be assessed on densely reconstructed regions and continually refined prior to landing. We simulated a mission scenario for approaching a hypothetical small body whose motion and shape were unknown a priori, starting from thousands of kilometers down to 20 km. Results indicate the feasibility of recovering the relative body motion and shape solely relying on onboard measurements and estimates with their associated uncertainties and without human input. Current work continues to mature and characterize the algorithms for the last phases of the estimation framework to land on the surface.

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“…Fesq et al [34] describes using the ASTERIA CubeSat to explore using Autonav for orbit determination by passively observing objects in space. One potential set of objects mentioned are satellites in a geostationary orbit (GEO).…”

Section: Geostationay Observationsmentioning

confidence: 99%

Nonlinear Estimation for Autonomous Optical Navigation

Hallgrimson¹

2021

Preprint

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Many interplanetary mission concepts can benefit from autonomous orbit estimation, particularly during critical mission phases. Previous studies have examined the feasibility of optical navigation using nanosatellite class instruments. While promising, these techniques are not without drawbacks. Convergence of the navigation estimates are often sensitive to errors in initial state estimates. This thesis compares various methods to perform nonlinear estimation for autonomous optical navigation. These methods include an extended Kalman filter (EKF), an unscented Kalman filter (UKF), a particle filter (PF), a fixed-lag smoother (FLS), and moving horizon estimation (MHE). The EKF, UKF, and PF can be implemented in real time, while the FLS and MHE implement a delay into the estimation process. To compare the performance of each state estimator three initial reference scenarios around Mars were considered: a hyperbolic flyby, an elliptic orbit and a orbital maneuver using observations of Mars and its moons. Parameter estimation was also explored, where the mass of Mars was to be estimated as a reference parameter in both the hyperbolic and elliptical trajectories. One last reference scenario included a low Earth orbit (LEO) using observations of satellites in a geosynchronous equatorial orbit. In each case, the FLS and MHE showed similar or better performance over each state estimator but at the cost of an increased computation time with respect to the reference EKF. Similarly the UKF was able to provide improved results withe respect to the EKF. While, the PF provided poor estimates in the Mars trajectories but improvements were seen from the UKF and EKF in the LEO scenario.

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Extended Mission Technology Demonstrations Using the ASTERIA Spacecraft

Cited by 18 publications

References 6 publications

Autonomy for Space Robots: Past, Present, and Future

Autonomy for Space Robots: Past, Present, and Future

Autonomous Exploration of Small Bodies Toward Greater Autonomy for Deep Space Missions

Nonlinear Estimation for Autonomous Optical Navigation

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