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Simultaneous Calibration Of Robotic Base And Tool
Published in Hanqi Zhuang, Zvi S. Roth, Camera-Aided Robot Calibration, 2018
In this type of test, the nominal PUMA geometry listed in Table 10.4.1 and noise level 1 listed in Table 10.4.2 were adopted. Figures 10.4.1 and 10.4.2 depict position and orientation errors against the number of pose measurements. The position error is defined as the norm of the difference between the computed position using the identified BASE and TOOL and the actual position obtained using the given BASE and TOOL. The orientation error is defined in a similar way.
Pedestrian positioning using smartphones in building with atypical geometry
Published in Soňa Molčíková, Viera Hurčíková, Vladislava Zelizňaková, Peter Blišťan, Advances and Trends in Geodesy, Cartography and Geoinformatics, 2018
E. Erdelyiova, P. Kajanek, A. Kopacik
IMS allows monitoring of pedestrian movement in three-dimensional space independently of external sources and in areas where GNSS signal is not available. On the other hand, functional principle of the IMS based on the integration of inertial measurements causes a rapid accumulation of systematic errors of inertial measurement in actual position and orientation. The actual position error is generated by the systematic errors of accelerometers and gyroscopes.
Monitoring GNSS signal quality at Zilina Airport
Published in Vladimír. Socha, Lenka Hanáková, Andrej Lališ, New Trends in Civil Aviation, 2018
P. Haljaková, A. Novák, J. Žižka
A receiver’s calculated position is determined by latitude, longitude, and altitude. GPS position error is the difference between calculated and actual positions. For any calculated position, the probability of not exceeding the required levels of accuracy should not be less than 95%.
Dose rate distribution measuring method using personal dosimeters and localization devices
Published in Journal of Nuclear Science and Technology, 2022
Daisuke Shinma, Yukihiro Murata, Yuichiro Ueno, Akihito Yamaguchi, Masahiro Tomizawa, Toshiya Yamano, Junichi Kitamura
PDR technologies use acceleration sensors. A position is estimated by the double integral of the acceleration. Therefore, a sensing error introduces position errors. This technology requires an absolute position calibration system, such as position markers, because a position error can be accumulated depending on the moving distance. Moreover, frequent absolute position calibration is required. A person who has a device using PDR technologies would need to stop by the absolute position calibration point regularly. It is not feasible to set positioning markers in actual plants and force workers to calibrate their positions repeatedly. In addition, the accuracy of this technology is affected by the user. Individual differences in walking style such as stride and body movement affect the position estimation accuracy. According to [6], the accumulated error was about 10 m after walking 1 km. To keep the error below 1 m, the worker needs to calibrate their position every 100 m. This is unrealistic because it interrupts the maintenance work and does not provide sufficient accuracy.
Autonomous underwater vehicles - challenging developments and technological maturity towards strategic swarm robotics systems
Published in Marine Georesources & Geotechnology, 2019
N. Vedachalam, R. Ramesh, V. Bala Naga Jyothi, V. Doss Prakash, G. A. Ramadass
The error model for the gyroscope, accelerometers and the DVL are based on the published models (Ramadass et al. 2013; Hegrenæs et al. 2016; Tal, Klein, and Katz 2017). The position drift in a DVL-aided INS is determined by the error in the estimated navigation frame velocity (N and E velocity). The main contributors for the position error are due to the errors in the body-frame velocity and heading measurements. The computational logic based on the described navigation equations, coriolis correction and the local gravitational field is shown in Figure 12.