Performance measurement and prediction in a distributed telerobotics system

Skubic, M.; Morgan, Bo; Graves, S.; Kondraske, George V.; Khoury, George J.; Fiedler, Petr

doi:10.1109/icsmc.1995.538093

Cited by 4 publications

(1 citation statement)

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“…͑Special-effects images created using photorealistic rover models and image mosaics acquired during their missions. Rover model size approximated based on size of rover tracks in actual mosaic.͒ Skubic et al ͑1995͒ introduced a good set of general metrics for predicting the performance of developmental telerobotics systems. They are mostly direct inverse relationships of single performance quantities ͑e.g., time to complete a task and average position error͒ and some simple ratios ͑e.g., distance per unit time and successes per average completion time͒.…”

Section: Related Workmentioning

confidence: 99%

Operational performance metrics for mars exploration rovers

Tunstel

2007

Journal of Field Robotics

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The concept of operational performance metrics and associated measurement issues is explored for deployed robotic systems. The focus is on performance of mobility and robotic arm autonomy exercised on the NASA Mars Exploration Rovers surface mission. This planetary rover mission has been underway for nearly 3 years since January 2004 using two rovers performing separate missions. The autonomy functions of surface navigation, short-distance approach to surface science targets, and robotic placement of armmounted instruments on science targets are considered. Operational metrics that measure performance of these functions relative to system requirements are advocated. Specific metrics are defined and computed using telemetry from the rovers' multiyear operations on Mars and applied to rate performance during their respective missions. An existing methodology is applied to compute metrics with respect to required performance and to aggregate multiple metrics into a composite performance score for each rover. The formulation is augmented to accommodate importance weights that add flexibility in use of the metrics by different potential endusers, e.g., sponsors, program managers, systems engineers, and technologists. A brief example illustrates the application and effect of importance weights on overall rover performance scores.

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Section: Related Workmentioning

confidence: 99%