Kalman Filter-based navigation system for the Amphibious Spherical Robot

Huiming Xing; Shuxiang Guo; Liwei Shi; Shaowu Pan; Yanlin He; Kun Tang; Shuxiang Su; Zhan Chen

doi:10.1109/ICMA.2017.8015891

Kalman Filter-based navigation system for the Amphibious Spherical Robot

Huiming Xing, Shuxiang Guo^*, Liwei Shi, Shaowu Pan, Yanlin He, Kun Tang, Shuxiang Su, Zhan Chen

^*Corresponding author for this work

School of Medical and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Citations (Scopus)

Abstract

Robust and performing navigation systems for Autonomous Underwater Vehicles (AUVs) play a discriminant role towards the success of complex underwater missions. This paper presents a new design and development of a low-cost INS (Inertial Navigation System) using Miro-Electro-Mechanical-System (MEMS) inertial sensor and the pressure sensor (PS). The intensive pre-processing and modeling MEMES sensor's primitive, noisy motion data are outline, these techniques transform the erroneous motion data into practical motion indicators illustrated in 3D position, 3D velocity and 3D orientation. INS acts as a dead reckoning device. The pressure sensor is used to detect the depth data of underwater Vehicles. The quality of the filtering algorithm for the estimation of the AUV navigation state strongly affects the performance of the overall system. In this paper, the authors present adapt the Kalman Filter (KF) approach. Experiments were conducted to improve the navigation system performance of the INS and PS installed on the Amphibious Spherical Robot III (ASR III) for motion and attitude estimation. Lastly the experiment results are evaluated and verified using the sensor data from the navigation system.

Original language	English
Title of host publication	2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	638-643
Number of pages	6
ISBN (Electronic)	9781509067572
DOIs	https://doi.org/10.1109/ICMA.2017.8015891
Publication status	Published - 23 Aug 2017
Event	14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 - Takamatsu, Japan Duration: 6 Aug 2017 → 9 Aug 2017

Publication series

Name	2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017

Conference

Conference	14th IEEE International Conference on Mechatronics and Automation, ICMA 2017
Country/Territory	Japan
City	Takamatsu
Period	6/08/17 → 9/08/17

Keywords

Amphibious Spherical Robot
Inertial Measurement System
Kalman Filter
Pressure Senor

Access to Document

10.1109/ICMA.2017.8015891

Cite this

Xing, H., Guo, S., Shi, L., Pan, S., He, Y., Tang, K., Su, S., & Chen, Z. (2017). Kalman Filter-based navigation system for the Amphibious Spherical Robot. In 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017 (pp. 638-643). Article 8015891 (2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMA.2017.8015891

@inproceedings{dbb6f5f016634523836347a7191bcdac,

title = "Kalman Filter-based navigation system for the Amphibious Spherical Robot",

abstract = "Robust and performing navigation systems for Autonomous Underwater Vehicles (AUVs) play a discriminant role towards the success of complex underwater missions. This paper presents a new design and development of a low-cost INS (Inertial Navigation System) using Miro-Electro-Mechanical-System (MEMS) inertial sensor and the pressure sensor (PS). The intensive pre-processing and modeling MEMES sensor's primitive, noisy motion data are outline, these techniques transform the erroneous motion data into practical motion indicators illustrated in 3D position, 3D velocity and 3D orientation. INS acts as a dead reckoning device. The pressure sensor is used to detect the depth data of underwater Vehicles. The quality of the filtering algorithm for the estimation of the AUV navigation state strongly affects the performance of the overall system. In this paper, the authors present adapt the Kalman Filter (KF) approach. Experiments were conducted to improve the navigation system performance of the INS and PS installed on the Amphibious Spherical Robot III (ASR III) for motion and attitude estimation. Lastly the experiment results are evaluated and verified using the sensor data from the navigation system.",

keywords = "Amphibious Spherical Robot, Inertial Measurement System, Kalman Filter, Pressure Senor",

author = "Huiming Xing and Shuxiang Guo and Liwei Shi and Shaowu Pan and Yanlin He and Kun Tang and Shuxiang Su and Zhan Chen",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 ; Conference date: 06-08-2017 Through 09-08-2017",

year = "2017",

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doi = "10.1109/ICMA.2017.8015891",

language = "English",

series = "2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017",

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Xing, H, Guo, S, Shi, L, Pan, S, He, Y, Tang, K, Su, S & Chen, Z 2017, Kalman Filter-based navigation system for the Amphibious Spherical Robot. in 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017., 8015891, 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017, Institute of Electrical and Electronics Engineers Inc., pp. 638-643, 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017, Takamatsu, Japan, 6/08/17. https://doi.org/10.1109/ICMA.2017.8015891

Kalman Filter-based navigation system for the Amphibious Spherical Robot. / Xing, Huiming; Guo, Shuxiang; Shi, Liwei et al.
2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 638-643 8015891 (2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Kalman Filter-based navigation system for the Amphibious Spherical Robot

AU - Xing, Huiming

AU - Guo, Shuxiang

AU - Shi, Liwei

AU - Pan, Shaowu

AU - He, Yanlin

AU - Tang, Kun

AU - Su, Shuxiang

AU - Chen, Zhan

PY - 2017/8/23

Y1 - 2017/8/23

N2 - Robust and performing navigation systems for Autonomous Underwater Vehicles (AUVs) play a discriminant role towards the success of complex underwater missions. This paper presents a new design and development of a low-cost INS (Inertial Navigation System) using Miro-Electro-Mechanical-System (MEMS) inertial sensor and the pressure sensor (PS). The intensive pre-processing and modeling MEMES sensor's primitive, noisy motion data are outline, these techniques transform the erroneous motion data into practical motion indicators illustrated in 3D position, 3D velocity and 3D orientation. INS acts as a dead reckoning device. The pressure sensor is used to detect the depth data of underwater Vehicles. The quality of the filtering algorithm for the estimation of the AUV navigation state strongly affects the performance of the overall system. In this paper, the authors present adapt the Kalman Filter (KF) approach. Experiments were conducted to improve the navigation system performance of the INS and PS installed on the Amphibious Spherical Robot III (ASR III) for motion and attitude estimation. Lastly the experiment results are evaluated and verified using the sensor data from the navigation system.

AB - Robust and performing navigation systems for Autonomous Underwater Vehicles (AUVs) play a discriminant role towards the success of complex underwater missions. This paper presents a new design and development of a low-cost INS (Inertial Navigation System) using Miro-Electro-Mechanical-System (MEMS) inertial sensor and the pressure sensor (PS). The intensive pre-processing and modeling MEMES sensor's primitive, noisy motion data are outline, these techniques transform the erroneous motion data into practical motion indicators illustrated in 3D position, 3D velocity and 3D orientation. INS acts as a dead reckoning device. The pressure sensor is used to detect the depth data of underwater Vehicles. The quality of the filtering algorithm for the estimation of the AUV navigation state strongly affects the performance of the overall system. In this paper, the authors present adapt the Kalman Filter (KF) approach. Experiments were conducted to improve the navigation system performance of the INS and PS installed on the Amphibious Spherical Robot III (ASR III) for motion and attitude estimation. Lastly the experiment results are evaluated and verified using the sensor data from the navigation system.

KW - Amphibious Spherical Robot

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KW - Pressure Senor

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DO - 10.1109/ICMA.2017.8015891

M3 - Conference contribution

AN - SCOPUS:85030311042

T3 - 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017

SP - 638

EP - 643

BT - 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017

Y2 - 6 August 2017 through 9 August 2017

ER -

Xing H, Guo S, Shi L, Pan S, He Y, Tang K et al. Kalman Filter-based navigation system for the Amphibious Spherical Robot. In 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 638-643. 8015891. (2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017). doi: 10.1109/ICMA.2017.8015891

Kalman Filter-based navigation system for the Amphibious Spherical Robot

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