TY - GEN
T1 - The integration of some sensors for measuring the attitudes of a Manta robot
AU - Deng, Liying
AU - Wang, Qiuying
AU - Mikuriya, Kota
AU - Watanabe, Keigo
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China(51509049).
Publisher Copyright:
© 2016 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/9/1
Y1 - 2016/9/1
N2 - The Manta robot is a kind of underwater robot that uses only one pair of right and left pectoral fins to produce swimming propulsive forces. The measurement system of a Manta robot used in this work includes a gyro, an accelerometer and a magnetometer. This paper is devoted to discuss the attitude determination algorithm of such a Manta Robot. Since the attitude determination combining the accelerometer and magnetometer measurements is only available when the robot is in a steady-state or of uniform motion, the gyro measurement is adopted to amend the attitude in a dynamic state by an unscented Kalman filter (UKF). What's more, the gyro has a drift, so that this error will be accumulated when the time goes on. Therefore, an autoregressive (AR) model is applied to model the stochastic drift of the gyro. The output of the gyro is denoised by the Kalman filter on the basis of this drift model. Finally, some experiments with a real robot are carried out to verify this plan.
AB - The Manta robot is a kind of underwater robot that uses only one pair of right and left pectoral fins to produce swimming propulsive forces. The measurement system of a Manta robot used in this work includes a gyro, an accelerometer and a magnetometer. This paper is devoted to discuss the attitude determination algorithm of such a Manta Robot. Since the attitude determination combining the accelerometer and magnetometer measurements is only available when the robot is in a steady-state or of uniform motion, the gyro measurement is adopted to amend the attitude in a dynamic state by an unscented Kalman filter (UKF). What's more, the gyro has a drift, so that this error will be accumulated when the time goes on. Therefore, an autoregressive (AR) model is applied to model the stochastic drift of the gyro. The output of the gyro is denoised by the Kalman filter on the basis of this drift model. Finally, some experiments with a real robot are carried out to verify this plan.
KW - AR model
KW - Attitude measurement
KW - Manta robot
KW - Unscented Kalman filter
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U2 - 10.1109/ICMA.2016.7558617
DO - 10.1109/ICMA.2016.7558617
M3 - Conference contribution
AN - SCOPUS:84991205068
T3 - 2016 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2016
SP - 519
EP - 524
BT - 2016 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2016
Y2 - 7 August 2016 through 10 August 2016
ER -