Mars Exploration Rover Surface Operations: Driving Spirit at Gusev Crater

Leger, Patrick C.; Trebi-Ollennu, A.; Wright, John R.; Maxwell, Scott; Bonitz, R.G.; Biesiadecki, Jeffrey J.; Hartman, Frank R.; Cooper, Brian; Baumgartner, Eric T.; Maimone, Mark

doi:10.1109/icsmc.2005.1571411

Cited by 68 publications

(47 citation statements)

References 11 publications

(9 reference statements)

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“…Being able to predict slip from a distance will have significant impact on future Mars rover missions, because slip has been recognized as one of the key limiting factors in the current Mars Exploration Rover (MER) mission [3], [16]. In our previous work [1], [2] we have shown the viability of the approach for prediction of slip at a future location.…”

Section: Introductionmentioning

confidence: 99%

Learning slip behavior using automatic mechanical supervision

Angelova

Matthies

Helmick

et al. 2007

Proceedings 2007 IEEE International Conference on Robotics and Automation

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Abstract-We address the problem of learning terrain traversability properties from visual input, using automatic mechanical supervision collected from sensors onboard an autonomous vehicle. We present a novel probabilistic framework in which the visual information and the mechanical supervision interact to learn particular terrain types and their properties.The proposed method is applied to learning of rover slippage from visual information in a completely automatic fashion. Our experiments show that using mechanical measurements as automatic supervision significantly improves the visual-based classification alone and approaches the results of learning with manual supervision. This work will enable the rover to drive safely on slopes, learning autonomously about different terrains and their slip characteristics.

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Section: Introductionmentioning

confidence: 99%

Learning slip behavior using automatic mechanical supervision

Angelova

Matthies

Helmick

et al. 2007

Proceedings 2007 IEEE International Conference on Robotics and Automation

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“…For example, the amount of solar energy available to the Mars Exploration Rovers (MER) restricts the number of operations they can perform on a given day (Leger et al, 2005;Biesiadecki et al, 2005). Their lack of autonomy is also very costly considering the twenty-minute communication delay between Mars and Earth (Norris et al, 2005).…”

Section: Motivationmentioning

confidence: 99%

Long‐range rover localization by matching LIDAR scans to orbital elevation maps

Carle¹,

Furgale²,

Barfoot³

2010

Journal of Field Robotics

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Output uncertainties were large due to large input uncertainties, but these could be reduced in future experimentation by minimizing the use of simulated input data. It was concluded that the architecture could be used to accurately and autonomously localize a rover over long-range traverses.ii Acknowledgements I owe greatest thanks to my supervisor Tim Barfoot for his generous guidance and razor-sharp honesty. Thanks to Joseph Bakambu for helpful discussions on feature matching techniques.

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“…Space agencies have had several high profile robotic projects, designed with an eye toward safely exploring remote planets and moons. Examples include early successes of the Soviet Lunokhods [52] and NASA's more recent success of exploring the surface of Mars [53,54].…”

Section: 2applicationsmentioning

confidence: 99%