دورية أكاديمية

Probabilistic Mapping with Ultrasonic Distance Sensors.

التفاصيل البيبلوغرافية
العنوان: Probabilistic Mapping with Ultrasonic Distance Sensors.
المؤلفون: Andersone, Ilze
المصدر: Procedia Computer Science; 2017, Vol. 104, p362-368, 7p
مصطلحات موضوعية: CARTOGRAPHY, ROBOTICS, PROBABILISTIC databases, ULTRASONIC imaging, GAUSSIAN processes
مستخلص: This paper proposes a probabilistic robotic mapping approach to merge ultrasonic distance readings by modelling them as Gaussian random variables and using scan matching to reduce uncertainty in mapping process. To account for the high angular uncertainty of ultrasonic distance sensors, both positive readings (detected objects) and negative readings (the lack of detection) are taken into account to update the measurements and create the updated environment map. To support this approach, the map consists simultaneously from two parts – free space scans are stored in occupancy grid and obstacle readings are represented as Gaussian variable feature set. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Supplemental Index
الوصف
تدمد:18770509
DOI:10.1016/j.procs.2017.01.146