Vision-based estimation of small body rotational state

Panicucci, Paolo; Lebreton, Jérémy; Brochard, Roland; Zenou, Emmanuel; Delpech, Michel

doi:10.1016/j.actaastro.2023.08.046

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…Among the various navigation alternatives for spacecraft, including autonomous X-ray pulsar-based [2], semi-autonomous radio-based navigation [3], and autonomous vision-based navigation (VBN), the latter is often preferred due to its reduced implementation cost, full ground independence, and applicability to different spacecraft classes [4]. In addition, VBN is an approach compatible with all mission phases toward celestial bodies: cruise [5][6][7][8], mid-range [9][10][11][12], and close proximity [13], including landing [14,15]. VBN allows probes to determine their state by observing celestial bodies on images taken by optical sensors and has already been adopted by various missions [16].…”

Section: Introductionmentioning

confidence: 99%

Hardware-In-the-Loop Validation of Autonomous Interplanetary Navigation Algorithms for Interplanetary Cruises with the Optical Star Stimulator

Andreis,

Krüger,

Woicke

et al. 2024

AIAA SCITECH 2024 Forum

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Thanks to the rising focus on deep-space exploration and exploitation, the demand for sustainable and efficient navigation approaches has become crucial. Standard ground-based radiometric tracking, while accurate, is expensive and resourceintensive, posing long-term sustainability challenges. Therefore, enhancing spacecraft autonomy is crucial to avoid ground station saturation. Autonomous onboard guidance, navigation, and control (GNC) offer cost reduction and expand interplanetary exploration opportunities. Among various navigation alternatives, vision-based navigation (VBN) stands out for its cost-effectiveness, ground independence, and applicability to different spacecraft classes. Ground testing campaigns are crucial to ensure accurate and robust vision-based navigation algorithms for interplanetary missions. However, obtaining real interplanetary sky-field images for validation is challenging due to limited successful missions and datasets. To overcome these limitations, high-fidelity rendering engines and hardware-in-the-loop (HIL) simulations are necessary to generate image datasets for testing. This work presents the development of a procedure for on-ground testing and validation of autonomous navigation algorithms for interplanetary cruises using Jena Optronik's Optical Sky Stimulator (OSI) at the DLR GNC Department in Bremen. The proposed paper includes preparation activities, calibration and compensation procedures, and final hardware-in-the-loop simulations.

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Section: Introductionmentioning

confidence: 99%

Hardware-In-the-Loop Validation of Autonomous Interplanetary Navigation Algorithms for Interplanetary Cruises with the Optical Star Stimulator

Andreis,

Krüger,

Woicke

et al. 2024

AIAA SCITECH 2024 Forum

Self Cite

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Initial Pole Axis and Spin Direction Estimation of Asteroids Using Infrared Imagery

Kuppa,

McMahon,

Dietrich

2024

Journal of Guidance, Control, and Dynamics

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Knowing the pole axis of an asteroid is vital to autonomous asteroid exploration efforts. Ground-based initial pole estimation methods are time and data intensive and produce estimates with large uncertainties. These errors have a significant impact on proximity navigation, shape modeling, and scientific data for small body missions. In this paper, a new method of obtaining this information from onboard spacecraft imagery is presented. The proposed method estimates the pole from onboard infrared imagery using the camera-asteroid geometry. This method does not require a prior and is designed to work in a vast majority approach trajectories due to the use of infrared images. The method is applied to simulated infrared images of asteroids 101955 Bennu and 25143 Itokawa as well as real infrared images of asteroid 162173 Ryugu from the Hayabusa2 mission. The average pole errors using this method on Bennu and Itokawa images are approximately 2 and 6 deg, respectively. The pole estimate error on the Ryugu images is approximately 8 deg. The algorithm is shown to be sensitive to the percentage of spin period imaged and the spacing between the images.

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Autonomous Vision-Based Algorithm for Interplanetary Navigation

Andreis,

Panicucci,

Topputo

2024

Journal of Guidance, Control, and Dynamics

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The surge of deep-space probes makes it unsustainable to navigate them with standard radiometric tracking. Autonomous interplanetary satellites represent a solution to this problem. In this work, a vision-based navigation algorithm is built by combining an orbit determination method with an image processing pipeline suitable for interplanetary transfers of autonomous platforms. To increase the computational efficiency of the algorithm, an extended Kalman filter is selected as state estimator, fed by the positions of the planets extracted from deep-space images. An enhancement of the estimation accuracy is performed by applying an optimal strategy to select the best pair of planets to track. Moreover, a novel analytical measurement model for deep-space navigation is developed providing a first-order approximation of the light-aberration and light-time effects. Algorithm performance is tested on a high-fidelity, Earth–Mars interplanetary transfer, showing the algorithm applicability for deep-space navigation.

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Vision-based estimation of small body rotational state

Cited by 3 publications

References 26 publications

Hardware-In-the-Loop Validation of Autonomous Interplanetary Navigation Algorithms for Interplanetary Cruises with the Optical Star Stimulator

Hardware-In-the-Loop Validation of Autonomous Interplanetary Navigation Algorithms for Interplanetary Cruises with the Optical Star Stimulator

Initial Pole Axis and Spin Direction Estimation of Asteroids Using Infrared Imagery

Autonomous Vision-Based Algorithm for Interplanetary Navigation

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