Correction Robot pose for SLAM based on Extended Kalman Filter in a Rough Surface Environment | Zendy

Jae-Yong Park | Zendy; Suk-Gyu Lee | Zendy; Joohyun Park | Zendy

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Correction Robot pose for SLAM based on Extended Kalman Filter in a Rough Surface Environment

Author(s) -

Jae-Yong Park,

Suk-Gyu Lee,

Joohyun Park

Publication year - 2009

Publication title -

international journal of advanced robotic systems

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.394

H-Index - 46

eISSN - 1729-8814

pISSN - 1729-8806

DOI - 10.5772/6789

Subject(s) - kalman filter , computer science , computer vision , artificial intelligence , robot , extended kalman filter , simultaneous localization and mapping , heading (navigation) , kinematics , fast kalman filter , mobile robot , filter (signal processing) , moving horizon estimation , engineering , physics , classical mechanics , aerospace engineering

This research deals with mobile robot SLAM algorithm based on extended kalman filter. To enhance a accuracy of robot pose, one more extended kalman filter is used in a rough surface environment. The robot has uncertain kinematic model due to a caterpillar. When the robot drives on irregular surface, it's heading can be corrupted. We propose a method to correct uncertain robot pose using one more extended kalman filter through simulation results

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