Robot path Planning Using  SIFT and Sonar Sensor Fusion

Alfredo Plascencia, Hector Raposo

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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
Original languageEnglish
Title of host publicationThe WSEAS International Conference on  Robotics, Control and Manufacturing Technology (ROCOM '07)
Number of pages6
PublisherWSEAS Press
Publication date2007
Pages251-256
ISBN (Print)978-960-8457-67-6
Publication statusPublished - 2007
EventWSEAS International Conference on  Robotics, Control and Manufacturing Technology (ROCOM '07) - Hangzhou, China
Duration: 15 Apr 200717 Apr 2007
Conference number: 7

Conference

ConferenceWSEAS International Conference on  Robotics, Control and Manufacturing Technology (ROCOM '07)
Number7
CountryChina
CityHangzhou
Period15/04/200717/04/2007

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    Plascencia, A., & Raposo, H. (2007). Robot path Planning Using  SIFT and Sonar Sensor Fusion. In The WSEAS International Conference on  Robotics, Control and Manufacturing Technology (ROCOM '07) (pp. 251-256). WSEAS Press.