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Infrastructure-Aided Localization and State Estimation for Autonomous Mobile Robots

Flögel, Daniel 1; Bhatt, Neel Pratik; Hashemi, Ehsan
1 Institut für Regelungs- und Steuerungssysteme (IRS), Karlsruher Institut für Technologie (KIT)

Abstract:

A slip-aware localization framework is proposed for mobile robots experiencing wheel slip in dynamic environments. The framework fuses infrastructure-aided visual tracking data (via fisheye lenses) and proprioceptive sensory data from a skid-steer mobile robot to enhance accuracy and reduce variance of the estimated states. The slip-aware localization framework includes: the visual thread to detect and track the robot in the stereo image through computationally efficient 3D point cloud generation using a region of interest; and the ego motion thread which uses a slip-aware odometry mechanism to estimate the robot pose utilizing a motion model considering wheel slip. Covariance intersection is used to fuse the pose prediction (using proprioceptive data) and the visual thread, such that the updated estimate remains consistent. As confirmed by experiments on a skid-steer mobile robot, the designed localization framework addresses state estimation challenges for indoor/outdoor autonomous mobile robots which experience high-slip, uneven torque distribution at each wheel (by the motion planner), or occlusion when observed by an infrastructure-mounted camera. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000151054
Veröffentlicht am 07.10.2022
Originalveröffentlichung
DOI: 10.3390/robotics11040082
Scopus
Zitationen: 9
Dimensions
Zitationen: 9
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Regelungs- und Steuerungssysteme (IRS)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2218-6581
KITopen-ID: 1000151054
Erschienen in Robotics
Verlag MDPI
Band 11
Heft 4
Seiten Art.Nr. 82
Vorab online veröffentlicht am 18.08.2022
Nachgewiesen in Dimensions
Scopus
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