Robot path Planning Using  SIFT and Sonar Sensor Fusion

Alfredo Plascencia, Hector Raposo

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Abstract

This paper presents a novel map building approach for path planning purposes, which takes into account the uncertainty inherent in sensor measurements. To this end, Bayesian estimation and Dempster-Shafer evidential theory are used to fuse the sensory information and to update the occupancy and evidential grid maps, respectively. The approach is illustrated using actual measurements from a laboratory robot. The sensory information is obtained from a sonar array and the Scale Invariant Feature Transform (SIFT) algorithm. Finally, the resulting two evidential maps based on Bayes and Dempster theories are used for path planning using the potential field method. Both yield satisfying results
OriginalsprogEngelsk
TitelThe WSEAS International Conference on  Robotics, Control and Manufacturing Technology (ROCOM '07)
Antal sider6
ForlagWSEAS Press
Publikationsdato2007
Sider251-256
ISBN (Trykt)978-960-8457-67-6
StatusUdgivet - 2007
BegivenhedWSEAS International Conference on  Robotics, Control and Manufacturing Technology (ROCOM '07) - Hangzhou, Kina
Varighed: 15 apr. 200717 apr. 2007
Konferencens nummer: 7

Konference

KonferenceWSEAS International Conference on  Robotics, Control and Manufacturing Technology (ROCOM '07)
Nummer7
Land/OmrådeKina
ByHangzhou
Periode15/04/200717/04/2007

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