Sensor Data Fusion for Body State Estimation in a Hexapod Robot With Dynamical Gaits

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dc.contributor.authorLin, Pei-Chun
dc.contributor.authorKoditschek, Daniel E
dc.contributor.authorKoditschek, Daniel E
dc.date2023-05-17T00:11:31.000
dc.date.accessioned2023-05-22T19:06:47Z
dc.date.available2023-05-22T19:06:47Z
dc.date.issued2006-10-01
dc.date.submitted2006-11-20T05:57:59-08:00
dc.description.abstractWe report on a hybrid 12-dimensional full body state estimator for a hexapod robot executing a jogging gait in steady state on level terrain with regularly alternating ground contact and aerial phases of motion. We use a repeating sequence of continuous time dynamical models that are switched in and out of an extended Kalman filter to fuse measurements from a novel leg pose sensor and inertial sensors. Our inertial measurement unit supplements the traditionally paired three-axis rate gyro and three-axis accelerometer with a set of three additional three-axis accelerometer suites, thereby providing additional angular acceleration measurement, avoiding the need for localization of the accelerometer at the center of mass on the robot’s body, and simplifying installation and calibration. We implement this estimation procedure offline, using data extracted from numerous repeated runs of the hexapod robot RHex (bearing the appropriate sensor suite) and evaluate its performance with reference to a visual ground-truth measurement system, comparing as well the relative performance of different fusion approaches implemented via different model sequences.
dc.description.commentsCopyright IEEE 2006. Reprinted from <em>IEEE Transactions on Robotics</em>, Volume 22, Issue 5, October 2006, pages 932-943. <br><br> This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
dc.identifier.urihttps://repository.upenn.edu/handle/20.500.14332/33391
dc.legacy.articleid1226
dc.legacy.fulltexturlhttps://repository.upenn.edu/cgi/viewcontent.cgi?article=1226&amp;context=ese_papers&amp;unstamped=1
dc.source.issue202
dc.source.journalDepartmental Papers (ESE)
dc.source.peerreviewedtrue
dc.source.statuspublished
dc.subject.otherGRASP
dc.subject.otherKodlab
dc.subject.otherextended kalman filter (ekf)
dc.subject.otherhybrid estimation model
dc.subject.otherinertial measurement unit (imu)
dc.subject.otherlegged robot
dc.subject.otherleg pose sensor (lps)
dc.subject.othersensor fusion
dc.titleSensor Data Fusion for Body State Estimation in a Hexapod Robot With Dynamical Gaits
dc.typeArticle
digcom.contributor.authorLin, Pei-Chun
digcom.contributor.authorKomsuoglu, Haldun
digcom.contributor.authorisAuthorOfPublication|email:kod@seas.upenn.edu|institution:University of Pennsylvania|Koditschek, Daniel E
digcom.identifierese_papers/202
digcom.identifier.contextkey225786
digcom.identifier.submissionpathese_papers/202
digcom.typearticle
dspace.entity.typePublication
relation.isAuthorOfPublicationb6e8657c-2331-43df-97c3-92e79f74a7be
relation.isAuthorOfPublicationb6e8657c-2331-43df-97c3-92e79f74a7be
relation.isAuthorOfPublication.latestForDiscoveryb6e8657c-2331-43df-97c3-92e79f74a7be
upenn.schoolDepartmentCenterDepartmental Papers (ESE)
upenn.schoolDepartmentCenterGeneral Robotics, Automation, Sensing and Perception Laboratory
upenn.schoolDepartmentCenterKod*lab
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