NDLI: Accurate perception of environmental ferrous features' positioning using a simple mobile robot platform

Content Provider	IEEE Xplore Digital Library
Author	Bastani, H. Mirmohammad-Sadeghi, H.
Copyright Year	2009
Description	Author affiliation: Smart Systems at Jacobs University Bremen, Germany (Bastani, H.) \|\| Communication Group Director of Information and Communication Technology Institute (ICTI), Isfahan University of Technology, Iran (Mirmohammad-Sadeghi, H.)
Abstract	Probabilistic perceptions are the most proper tools for building mobile robotics mapping especially if no accurate model of the sensory system and the environmental features are in hand. Here, we briefly introduce architecture of our Demining Robot (DR) and then deeply investigate the scanning and mapping method it employs in order to gather the knowledge from the working environment, communicate to the central point, polish the gathered data with a proper mathematical model, and indeed generate the output such that represents the hidden ferrous features of the work space. Since electromagnetic sensors are not accurate enough to include ranging information, a probabilistic model enriched with a filtering technique has significantly enhanced the location accuracy of the mapped features to reach the quality of 99.247% in average. Full autonomy of the robot for scanning the unknown features, eases the raw-data acquisition procedure for an on/offline refinement of white thermal random electromagnetic noise on the sensors. Depending on the application, false alarm and false negative thresholds are flexible to be defined with respect to the achievable mapping resolution.
Starting Page	1
Ending Page	6
File Size	838502
Page Count	6
File Format	PDF
ISBN	9781424448555
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-22
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	GPS Gesellschaft
Subject Keyword	Mobile robots Robot sensing systems Sensor phenomena and characterization Buildings Mathematical model Electromagnetic modeling Information filtering Information filters Orbital robotics Electromagnetic interference map quality Mobile robot environmental features probability modeling
Content Type	Text
Resource Type	Article

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