Automated Generation of Image Products for Mars Exploration Rover Mission Tactical Operations

Alexander, D.; Zamani, Payam; Deen, R.; Andres, P.; Mortensen, Helen B.

doi:10.1109/icsmc.2005.1571264

Cited by 8 publications

(4 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The need for camera images to be processed and delivered in a compressed time frame induced MIPL to develop a product generation and delivery pipeline that was robust and almost completely autonomous in its operation. This section presents a brief overview of the pipeline's design and identifies the interconnecting process streams; see Alexander et al [2005] for more details.…”

Section: Pipeline Design and Implementationmentioning

confidence: 99%

Processing of Mars Exploration Rover imagery for science and operations planning

et al. 2006

View full text Add to dashboard Cite

[1] The twin Mars Exploration Rovers (MER) delivered an unprecedented array of image sensors to the Mars surface. These cameras were essential for operations, science, and public engagement. The Multimission Image Processing Laboratory (MIPL) at the Jet Propulsion Laboratory was responsible for the first-order processing of all of the images returned by these cameras. This processing included reconstruction of the original images, systematic and ad hoc generation of a wide variety of products derived from those images, and delivery of the data to a variety of customers, within tight time constraints. A combination of automated and manual processes was developed to meet these requirements, with significant inheritance from prior missions. This paper describes the image products generated by MIPL for MER and the processes used to produce and deliver them.

show abstract

Section: Pipeline Design and Implementationmentioning

confidence: 99%

Processing of Mars Exploration Rover imagery for science and operations planning

et al. 2006

View full text Add to dashboard Cite

show abstract

“…To avoid an obstacle and plan a path, the Mars exploration rover (MER) generated a three-dimensional (3D) topographic map with stereo vision (Deen and Lorre, 2005;Wright et al, 2005;Cheng et al, 2006). Actual work indicated that the navigating error was less than 1 cm within 1 m. In Ralter, a sample of Lunar rover, two charge-coupled device (CCD) cameras were used as stereo vision sensors (Alexander et al, 2005;Litwin and Maki, 2005;Biesiadecki et al, 2005). In the system, images were subdivided and partially resampled to improve the matching speed.…”

Section: Introductionmentioning

confidence: 99%

A machine vision based autonomous navigation system for Lunar rover: the model and key technique

Zhong

2016

View full text Add to dashboard Cite

Purpose This study aims to find a feasible precise navigation model for the planed Lunar rover. Autonomous navigation is one of the most important missions in the Chinese Lunar exploration project. Machine vision is expected to be a promising option for this mission because of the dramatic development of an image processing technique. However, existing attempts are often subject to low accuracy and errors accumulation. Design/methodology/approach In this paper, a novel autonomous navigation model was developed, based on the rigid geometric and photogrammetric theory, including stereo perception, relative positioning and absolute adjustment. The first step was planned to detect accurate three-dimensional (3D) surroundings around the rover by matching stereo-paired images; the second was used to decide the local location and orientation changes of the rover by matching adjacent images; and the third was adopted to find the rover’s location in the whole scene by matching ground image with satellite image. Among them, the SURF algorithm that had been commonly believed as the best algorithm for matching images was adopted to find matched images. Findings Experiments indicated that the accurate 3D scene, relative positioning and absolute adjustment were easily generated and illustrated with the matching results. More importantly, the proposed algorithm is able to match images with great differences in illumination, scale and observation angle. All experiments and findings in this study proved that the proposed method could be an alternative navigation model for the planed Lunar rover. Originality/value With the matching results, an accurate 3D scene, relative positioning and absolute adjustment of rover can be easily generated. The whole test proves that the proposed method could be a feasible navigation model for the planed Lunar rover.

show abstract

“…The camera hardware (and associated software) has functioned nominally since landing. The cameras and flight software have been utilized as expected, and the ground software has performed extremely well -over 750,000 derived image products have been generated on the ground [8].…”

Section: Mer Surface Imaging Operationsmentioning

confidence: 99%

“…Aspects of the MER ground image processing software are described in detail in [2], [8] and [9]. The ground image processing software decompresses the image data, assembles ancillary information into the image header, and writes the image to an Experiment Data Record (EDR) file in PDS (Planetary Data System) format.…”

Section: Ground Softwarementioning

confidence: 99%

Operation and Performance of the Mars Exploration Rover Imaging System on the Martian Surface

Maki

Litwin

Schwochert

et al.

2005 IEEE International Conference on Systems, Man and Cybernetics

View full text Add to dashboard Cite

show abstract

Automated Generation of Image Products for Mars Exploration Rover Mission Tactical Operations

Cited by 8 publications

References 4 publications

Processing of Mars Exploration Rover imagery for science and operations planning

Processing of Mars Exploration Rover imagery for science and operations planning

A machine vision based autonomous navigation system for Lunar rover: the model and key technique

Operation and Performance of the Mars Exploration Rover Imaging System on the Martian Surface

Contact Info

Product

Resources

About