An aerobot for global in situ exploration of Titan

Hall, Jeffrey L.; Kerzhanovich, V. V.; Yavrouian, A.; Jones, Jack A.; White, Cheryl; Dudik, Brenda; Plett, G. A.; Mennella, Jerami; Elfes, Alberto

doi:10.1016/j.asr.2004.11.033

Cited by 26 publications

(11 citation statements)

References 7 publications

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“…Downlink bandwidth is expected to be 4,500 bits per second, or 130 Mbits per day assuming an 8 hour transmission window. 2 Autonomous methods of classifying aerial image data could preselect the most scientifi cally meaningful data for return to Earth. For example, spacecraft could transmit a representative sample of different image contents or prioritize specifi c features of interest.…”

Section: Future Mission Challengesmentioning

confidence: 99%

Using Onboard Clustering to Summarize Remotely Sensed Imagery

et al. 2010

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to distance, visibility constraints, and competing mission downlinks. Long missions and highresolution, multispectral imaging devices easily produce data exceeding the available bandwidth. As an example, the HiRISE camera aboard the Mars Reconnaissance Orbiter produces images of up to 16.4 Gbits in data volume but downlink bandwidth is limited to 6 Mbits per second (Mbps).To address this situation, the Jet Propulsion Laboratory has developed computationally efficient algorithms for analyzing science imagery onboard spacecraft. These algorithms autonomously cluster the data into classes of similar imagery. This enables selective downlink of representatives of each class and a map classifying the imaged terrain rather than the full data set, reducing downlinked data volume. This article demonstrates the method on an Earth-based aerial image data set. We examine a range of approaches including k-means clustering using image features based on color, texture, temporal, and spatial arrangement and compare it to the manual clustering of a fi eld expert. In doing so, we demonstrate the potential for such summarization algorithms to enable effective exploratory science despite limited downlink bandwidth.

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Section: Future Mission Challengesmentioning

confidence: 99%

Using Onboard Clustering to Summarize Remotely Sensed Imagery

et al. 2010

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“…Friedlander [32]. Studies [33][34][35][36][37][38] of Titan Montgolfière carried over the years can be found in the literature.…”

Section: Balloons For Exploring Titanmentioning

confidence: 99%

Planetary balloons

Blamont¹

2008

Exp Astron

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“…The above results strongly suggest jettisoning the gas tank after deployment and inflation of a blimp/balloon in the martian atmosphere and to possibly maintain a smaller tank for altitude changes and gas replenishment for the duration of the mission. An exploration of Titan with airships (e.g., [23]) is an ideal scenario for a tier-scalable mission in conjunction with an orbiter and ground-probing agents, because of the 1.5 times thicker atmosphere compared to Earth and the colder temperatures compared to Venus' surface and near-surface atmospheric temperatures.…”

Section: Tier-scalable Reconnaissance -Operational Control and Techmentioning

confidence: 99%

“…They are (1) simple in structure; (2) light-weight; (3) "easily" deployable (e.g., [22]), both in mid-air and from the surface; (4) buoyant without the need for propellant, (5) could operate without active flight control system (e.g., wind-driven), and (6) allow for extended mission durations, ranging from months to more than a year (e.g., [23]) and for repeated surface/subsurface sampling. Furthermore, equipped with either solar cells/batteries or RTGs, they can be electrically operated to support onboard instruments, data analysis capabilities, and active thrusting.…”

Section: Tier-scalable Reconnaissance -Operational Control and Techmentioning

confidence: 99%

Tier-Scalable Reconnaissance Missions For The Autonomous Exploration Of Planetary Bodies

Fink

Dohm

Tarbell

et al. 2007

2007 IEEE Aerospace Conference

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Abstract-A fundamentally new (scientific) reconnaissance mission concept, termed tier-scalable reconnaissance, for remote planetary (including Earth) atmospheric, surface and subsurface exploration recently has been devised [1][2][3][4][5] that soon will replace the engineering and safety constrained mission designs of the past, allowing for optimal acquisition of geologic, paleohydrologic, paleoclimatic, and possible astrobiologic information of Venus, Mars, Europa, Ganymede, Titan, Enceladus, Triton, and other extraterrestrial targets [6,7]. This paradigm is equally applicable to potentially hazardous or inaccessible operational areas on Earth such as those related to military or terrorist activities, or areas that have been exposed to biochemical agents, radiation, or natural disasters. Traditional missions have performed local, ground-level reconnaissance through rovers and immobile landers, or global mapping performed by an orbiter. The former is safety and engineering constrained, affording limited detailed reconnaissance of a single site at the expense of a regional understanding, while the latter returns immense datasets, often overlooking detailed information of local and regional significance.

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An aerobot for global in situ exploration of Titan

Cited by 26 publications

References 7 publications

Using Onboard Clustering to Summarize Remotely Sensed Imagery

Using Onboard Clustering to Summarize Remotely Sensed Imagery

Planetary balloons

Tier-Scalable Reconnaissance Missions For The Autonomous Exploration Of Planetary Bodies

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