The Mars exploration rovers descent image motion estimation system

Cheng, Yang; Goguen, J. D.; Johnson, Andrew; Leger, Chris; Matthies, Larry; Martin, Miguel San; Willson, Reg G.

doi:10.1109/mis.2004.18

Cited by 83 publications

(23 citation statements)

References 2 publications

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“…Recognitions of impact craters have revealed lots of findings [4], [6], [7], [10]. Surface dating is one of the most common applications by the analysis of the size and distribution frequency of craters, indicating that a catalogue with the size and distribution is very useful in combination with the Digital Elevation Model (DEM) data [5].…”

Section: Introductionmentioning

confidence: 99%

Automatic recognition of Martian craters based on MOLA-derived digital topography

Jin

Zhang

2013

2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA)

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The recognition of impact craters can provide information on impact craters' history and Martian evolution processes as well as for Martian rover landing site. Most previous studies about machine detection of impact craters on Mars are based on imagery data, however, it has large uncertainty in image processing. In this study, we present a novel approach for automatic recognition of impact craters based on the Mars Orbiter Laser Altimeter (MOLA)-derived digital topography data. Topographic curvature, which delineates impact crater on Digital Elevation Model (DEM), can be deduced from topography data. The thresholding map of curvature is transformed into a binary map, from which we can detect impact craters by combination of segmentation and flooding algorithms. More impact craters on Mars with confirmation algorithm can be effectively distinguished truly, which are added the existing catalog of manually identified Martian craters. It will be more useful for the study on impact craters' history and Martian evolution processes as well as Martian rover landing navigation.

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Section: Introductionmentioning

confidence: 99%

Automatic recognition of Martian craters based on MOLA-derived digital topography

Jin

Zhang

2013

2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA)

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“…Jet Propulsion Laboratory(JPL)'s Descent Image Motion Estimation System(DIMES) is the first optical navigation in the world for probe landing. On possible to autonomously process and react to imagery during landing on the Mars [4]. Feature detection and tracking is the first and important step for spacecraft or probe optical navigation.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Craters Detection from Planetary Image

Ding

Cao

2008

2008 3rd International Conference on Innovative Computing Information and Control

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As development of deep space exploration, the Guidance, Navigation and Control (GNC) technology of spacecraft or probe is becoming more important than ever. Vision-based navigation (optical navigation) is a good method to achieve autonomous landing of spacecraft. Therefore, the landmark has to be detected for Vision-based navigation. Craters are commonly found on the surface of planets, satellites, asteroids and other solar system bodies. Currently, the most of optical landmark navigation algorithm are built on the craters detection and tracking. The focus of this paper is to present an algorithm for autonomous crater detection. The whole course of crater detection can be divided into two steps, Multi-resolution feature points extraction and crater detection. The first step can be further divided into Multi-resolution window-based feature points' extraction and crater candidate area choice. The second step can be further divided into region growing, pixels of crater edge extraction, ellipse detection and obtaining craters. Experimental studies demonstrate that the detection rate of this algorithm is higher than 90% for image where the distribution of craters is discrete. Cao Yun-feng received M.E in School of

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“…Brightness Compensation: MER A and B arrived at Mars when Mars is 1.5 AU from the sun. At this distance the sunlight on Mars was (1/1.5) 2 or 44% of the intensity experienced on earth. To compensate for the brighter conditions the field test camera used a darker ND filter.…”

Section: B Field Test Sensorsmentioning

confidence: 94%

“…Below we briefly describe the single feature horizontal velocity estimation procedure and then we describe how it is applied multiple times to produce the final robust estimate of horizontal velocity. For additional details the reader should refer to [2].…”

Section: Algorithmmentioning

confidence: 99%

Field Testing of the Mars Exploration Rovers Descent Image Motion Estimation System

Johnson

Willson²,

Goguen

et al.

Proceedings of the 2005 IEEE International Conference on Robotics and Automation

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-The Mars Exploration Rover (MER) DescentImage Motion Estimation System (DIMES) is the first autonomous machine vision system used to safely land a robotics payload on another planet. DIMES consists of a descent camera and an algorithm for estimating horizontal velocity using image, inertial and altitude measurements. Before DIMES was accepted by MER for inclusion in the mission, its performance was validated through field testing using a manned helicopter to image three Mars analog test sites. Statistical analysis of the resulting 1900+ test cases showed that DIMES met its velocity estimation requirement. This paper describes the DIMES field test approach and associated results.Index Terms -Mars Landing, v e l o c i t y estimation, feature tracking, MER

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The Mars exploration rovers descent image motion estimation system

Cited by 83 publications

References 2 publications

Automatic recognition of Martian craters based on MOLA-derived digital topography

Automatic recognition of Martian craters based on MOLA-derived digital topography

Autonomous Craters Detection from Planetary Image

Field Testing of the Mars Exploration Rovers Descent Image Motion Estimation System

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