Multi-sensor Fusion Incorporating Adaptive Transformation for Reconfigurable Pavement Sweeping Robot

A. P. Povendhan, Lim Yi, A. A. Hayat, Anh Vu Le, K. L.J. Kai, B. Ramalingam, M. R. Elara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

An efficient sensors fusion framework in an autonomous robot is necessary for various functions like object detection and perception enhancement. Multi-sensor calibration techniques are used to fuse multiple static sensors into a single frame of reference. However, for reconfigurable robots, sensors can change pose during reconfiguration need a robust adaptive sensor fusion to account for the relative change in sensor position and orientation. We propose an adaptive sensor fusion framework that can be implemented on any reconfiguration robot to adjust calibration parameters. Our paper formulated an adaptive sensor fusion method, implemented it in real-time on an autonomous reconfigurable pavement sweeping robot called Panthera, and demonstrated qualitatively the accuracy of the proposed sensor fusion framework for environment perception during robot reconfiguring on the pavement.

Original languageEnglish
Title of host publication2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages300-306
Number of pages7
ISBN (Electronic)9781665417143
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021 - Prague, Czech Republic
Duration: Sept 27 2021Oct 1 2021

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Conference

Conference2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2021
Country/TerritoryCzech Republic
CityPrague
Period9/27/2110/1/21

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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