2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566) 2004
DOI: 10.1109/iros.2004.1389321
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Sensor based robot localisation and navigation: using interval analysis and unscented Kalman filter

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Cited by 30 publications
(24 citation statements)
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“…Following this, UKF approximates state and output mean and covariance more accurately than EKF and thus superior operation of UKF compared to EKF is expected. UKF was already used for mobile robot localization in Ashokaraj et al (2004) to fuse several sources of observations, and the estimates were, if necessary, corrected using interval analysis on sonar measurements. Here we use sonar measurements within UKF, without any other sensors except the encoders to capture angular velocities of the drive wheels (motion model inputs), and without any additional estimate corrections.…”
Section: Ukf Localizationmentioning
confidence: 99%
“…Following this, UKF approximates state and output mean and covariance more accurately than EKF and thus superior operation of UKF compared to EKF is expected. UKF was already used for mobile robot localization in Ashokaraj et al (2004) to fuse several sources of observations, and the estimates were, if necessary, corrected using interval analysis on sonar measurements. Here we use sonar measurements within UKF, without any other sensors except the encoders to capture angular velocities of the drive wheels (motion model inputs), and without any additional estimate corrections.…”
Section: Ukf Localizationmentioning
confidence: 99%
“…for i in [1,6] and 3 additional constraints ||B i B j || 2 = d 2 ij for i, j in [1,3], i = j in which d ij are known distances. This set of 9 equations in 9 unknowns has the advantage that the variables appear only once in each equation and consequently there will be no overestimation during the interval evaluation.…”
Section: Kinematicsmentioning
confidence: 99%
“…It has been early used for solving the inverse kinematics problem for serial 6R robot [14] but recent advances in this method has motivated recent works: clearance effect on robot [18], robot reliability [2], localization and navigation [1,4,17], motion planning [13], collision detection [15], calibration [5] to name a few. From the numerical view point the main advantages of this approach are flexibility (many different problems may be considered) and guaranteed results (no solution may be lost) as numerical round-off errors are taken into account.…”
Section: Introductionmentioning
confidence: 99%
“…• a mobile robot's localization and navigation (Ashokaraj et al, 2004;Clerentin et al, 2003;Kieffer et al, 2000;Seignez et al, 2005), and simultaneous localization and mapping (SLAM) (Drocourt et al, 2003),…”
Section: Robotics and Certificationmentioning
confidence: 99%