NDLI: Feature Chain Based Occupancy Grid SLAM for Robots Equipped with Sonar Sensors

Content Provider	IEEE Xplore Digital Library
Author	Pandey, A.K. Krishna, K.M. Hexmoor, H.
Copyright Year	2007
Description	Author affiliation: Robotics Res. Center, Int. Inst. of Inf. Technol., Hyderabad (Pandey, A.K.; Krishna, K.M.)
Abstract	This paper presents a methodology for achieving SLAM onto the occupancy grid framework with the data only from sonar sensors. Sonar data are highly noisy and unpredictable. Sonar does not give the consistent readings for a point from two different positions, so the approaches which rely on correspondence reading matching will prone to fail without exhaustive mathematical calculations of sonar modeling and environment modeling. Also, if features are being use to localize then the robot needs to revisit those features exactly, to localize, which itself will not be accurate because robot will not be at the exact position from where that feature has been detected. Hence it will not get back those feature readings using sonar. Here we are presenting a hybrid approach based on feature chain. Instead of relying completely on feature mapping and point matching, it finds the links between features to localize. It will drastically reduce the need of revisiting a feature to localize and hence reducing the exploration overhead, while handling other issues of problems with point or feature matching. We map features onto occupancy grid (OG) framework taking advantage of its dense representation of the world. Combining features onto OG overcomes many of its limitations such as the independence assumption between cells and provides for better modeling of the sonar implicitly providing more accurate maps
Starting Page	283
Ending Page	288
File Size	4838040
Page Count	6
File Format	PDF
ISBN	1424409446
DOI	10.1109/KIMAS.2007.369823
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-04-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer vision Simultaneous localization and mapping Uncertainty Working environment noise Sonar Indoor environments Robot sensing systems Mathematical model Optical reflection Information technology
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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