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

N. Rowell, M. N. Dunstan, S. M. Parkes, J. Gil-Fernández, I. Huertas, S. Salehi

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1193-1222
Number of pages30
JournalAeronautical Journal
Volume119
Issue number1220
DOIs
Publication statusPublished - 1 Oct 2015

Fingerprint

Asteroids
Navigation
Spacecraft
Visibility
Refining
Luminance
Lighting
Cameras

Cite this

Rowell, N. ; Dunstan, M. N. ; Parkes, S. M. ; Gil-Fernández, J. ; Huertas, I. ; Salehi, S. / Autonomous visual recognition of known surface landmarks for optical navigation around asteroids. In: Aeronautical Journal. 2015 ; Vol. 119, No. 1220. pp. 1193-1222.
@article{06042887ad6c47dcae67305b4a5e4b8c,
title = "Autonomous visual recognition of known surface landmarks for optical navigation around asteroids",
abstract = "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.",
author = "N. Rowell and Dunstan, {M. N.} and Parkes, {S. M.} and J. Gil-Fern{\'a}ndez and I. Huertas and S. Salehi",
year = "2015",
month = "10",
day = "1",
doi = "10.1017/S0001924000011210",
language = "English",
volume = "119",
pages = "1193--1222",
journal = "Aeronautical Journal",
issn = "0001-9240",
publisher = "Cambridge University Press",
number = "1220",

}

Autonomous visual recognition of known surface landmarks for optical navigation around asteroids. / Rowell, N.; Dunstan, M. N.; Parkes, S. M.; Gil-Fernández, J.; Huertas, I.; Salehi, S.

In: Aeronautical Journal, Vol. 119, No. 1220, 01.10.2015, p. 1193-1222.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Autonomous visual recognition of known surface landmarks for optical navigation around asteroids

AU - Rowell, N.

AU - Dunstan, M. N.

AU - Parkes, S. M.

AU - Gil-Fernández, J.

AU - Huertas, I.

AU - Salehi, S.

PY - 2015/10/1

Y1 - 2015/10/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84946828656&partnerID=8YFLogxK

U2 - 10.1017/S0001924000011210

DO - 10.1017/S0001924000011210

M3 - Article

VL - 119

SP - 1193

EP - 1222

JO - Aeronautical Journal

JF - Aeronautical Journal

SN - 0001-9240

IS - 1220

ER -