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dc.contributor.authorLubbe, Estelle
dc.contributor.authorUren, Kenneth R.
dc.contributor.authorWithey, Daniel
dc.identifier.citationLubbe, E. et al. 2015. State estimation for a hexapod robot. 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Congress Center, Hamburg, Sept 28 - Oct 2, 2015. Hamburg, Germany: 6286-6291. []en_US
dc.identifier.isbn978-1-4799-9994-1 (Online)
dc.description.abstractThis paper introduces a state estimation methodology for a hexapod robot that makes use of proprioceptive sensors and a kinematic model of the robot. The methodology focuses on providing reliable full pose state estimation for a commercially-available hexapod robot platform with the use of only commonly-available sensors. The presented methodology provides the derivation of the kinematic model and implements an Extended Kalman Filter (EKF) state estimation framework similar to that recently validated on a quadruped. The EKF fuses the kinematic model with on-board IMU measurements to estimate the pose of the robot. The methodology was tested with experiments using a physical hexapod robot and validated with independent ground truth measurementsen_US
dc.subjectRobot sensing systemsen_US
dc.subjectLegged locomotionen_US
dc.subjectRobot kinematicsen_US
dc.titleState estimation for a hexapod roboten_US
dc.contributor.researchID12064203 - Uren, Kenneth Richard

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