Image Processing for Near Earth Object Optical Guidance Systems

Rowell, N.; Parkes, Steve; Dunstan, Martin

doi:10.1109/taes.2013.6494399

Cited by 13 publications

(4 citation statements)

References 17 publications

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“…. (19) The objective function for the problem is the total covariance weighted reprojection error, which is the sum of the geometric distance between observed and projected landmarks weighted by S M -1 , and coincides with the chi-square statistic:…”

Section: (15)mentioning

confidence: 99%

Autonomous visual recognition of known surface landmarks for optical navigation around asteroids

et al. 2015

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We present an autonomous visual landmark recognition and pose estimation algorithm designed for use in navigation of spacecraft around small asteroids. Landmarks are selected as generic points on the asteroid surface that produce strong Harris corners in an image under a wide range in viewing and illumination conditions; no particular type of morphological feature is required. The set of landmarks is triangulated to obtain a tightly fitting mesh representing an optimal low resolution model of the natural asteroid shape, which is used onboard to determine the visibility of each landmark and enables the algorithm to work with highly concave bodies. The shape model is also used to estimate the centre of brightness of the asteroid and eliminate large translation errors prior to the main landmark recognition stage. The algorithm works by refining an initial estimate of the spacecraft position and orientation. Tests with real and synthetic images show good performance under realistic noise conditions. Using simulated images, the median landmark recognition error is 2m, and the error on the spacecraft position in the asteroid body frame is reduced from 45m to 21m at a range of 2km from the surface. With real images the translation error at 8km to the surface increases from 107m to 119m, due mainly to the larger range and lack of sensitivity to translations along the camera boresight. The median number of landmarks detected in the simulated and real images is 59 and 44 respectively. This algorithm was partly developed and tested during industrial studies for the European Space Agency’s Marco Polo-R asteroid sample return mission.

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Section: (15)mentioning

confidence: 99%

Autonomous visual recognition of known surface landmarks for optical navigation around asteroids

et al. 2015

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“…For example, approximately seven tracks are sufficient to reproduce the motion of the spacecraft in relation to the surface. To evaluate the response of the models to a realistic image processing navigation scenario, a feature tracking algorithm [12] based on the Harris corner detector was applied to image sequences approaching synthetic asteroid models Three image sequences are shown pictorially in Figure 10 where the lines represent feature points tracked across multiple images in the motion sequence. The top left image shows a tumbling synthetic asteroid and a stationary camera position, the top right image shows an approach towards another tumbling synthetic asteroid.…”

Section: Feature Trackingmentioning

confidence: 99%

Asteroid Modeling for Testing Spacecraft Approach and Landing

Martin

Parkes

Dunstan

et al. 2014

IEEE Comput. Grap. Appl.

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Abstract-Spacecraft exploration of asteroids presents a variety of autonomous navigation challenges that can be aided by virtual models to test and develop guidance and hazard avoidance systems. This paper describes the extension and application of graphics techniques to create high-resolution, virtual asteroid models to simulate cameras and other spacecraft sensors approaching and descending towards asteroids. A scalable model structure with evenly spaced vertices is specified to simplify terrain modeling, avoid distortion at the poles and enable triangle strip definition for efficient rendering. The base asteroid models are created using both a two-phase Poisson faulting technique and Perlin noise. Realistic asteroid surfaces are created by adding synthetic crater models adapted from lunar terrain simulation and multi-resolution boulders to the base models. The synthetic asteroids are evaluated by comparison with real asteroid images, slope distributions, and by applying a surface relative feature tracking algorithm to the models.

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“…In the past decade, efforts for the improvement of autonomous navigation capabilities have continued, employing observations of visible celestial bodies [10][11][12][13], observations of the Sun [14,15], distant stars [16,17], X-ray pulsar-based observations [18][19][20], and close-proximity observations of small bodies [21][22][23][24][25]. With the recent emergence of low-cost smallspacecraft technology, autonomous deep-space navigation is once again essential to reduce ground operations and overall mission costs.…”

Section: Introductionmentioning

confidence: 99%

CubeSat Autonomous Navigation and Guidance for Low-Cost Asteroid Flyby Missions

Machuca

Sánchez

2021

Journal of Spacecraft and Rockets

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Recent advancements in CubeSat technology unfold new mission ideas and the opportunity to lower the cost of space exploration. Ground operations costs for interplanetary CubeSats, however, still represent a challenge towards low-cost CubeSat missions: hence, certain levels of autonomy are desirable. The feasibility of autonomous asteroid flyby missions using CubeSats is assessed here, and an effective strategy for autonomous operations is proposed. The navigation strategy is composed of observations of the Sun, visible planets, and the target asteroid, whereas the guidance strategy is composed of two optimally-timed trajectory correction maneuvers. A Monte Carlo analysis is performed to understand the flyby accuracies that can be achieved by autonomous CubeSats, in consideration of errors and uncertainties in: (a) departure conditions, (b) propulsive maneuvers, (c) observations, and (d) asteroid ephemerides. Flyby accuracies better than ±100 km (3σ) are found possible, and main limiting factors to autonomous missions are identified, namely: (a) on-board asteroid visibility time (Vlim≥11), (b) ΔV for correction maneuvers (>15 m/s), (c) asteroid ephemeris uncertainty (<1000 km), and (d) short duration of transfer to asteroid. Ultimately, this study assesses the readiness level of current CubeSat technology to autonomously flyby near-Earth asteroids, in consideration of realistic system specifications, errors and uncertainties.

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Image Processing for Near Earth Object Optical Guidance Systems

Cited by 13 publications

References 17 publications

Autonomous visual recognition of known surface landmarks for optical navigation around asteroids

Autonomous visual recognition of known surface landmarks for optical navigation around asteroids

Asteroid Modeling for Testing Spacecraft Approach and Landing

CubeSat Autonomous Navigation and Guidance for Low-Cost Asteroid Flyby Missions

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