TY - GEN
T1 - Multi-Sensor Fusion Based Localization System for an Amphibious Spherical Robot
AU - Liu, Yu
AU - Guo, Shuxiang
AU - Shi, Liwei
AU - Xing, Huiming
AU - Hou, Xihuan
AU - Liu, Huikang
AU - Hu, Yao
AU - Xia, Debin
AU - Li, Zan
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Many techniques for robot localization rely on inertial navigation system which suffers from drift and huge computational cost. So, this paper presents a localization method which has a good real-time performance, high-precision and low-cost assumption for a compact amphibious spherical robot. Specifically, this system can navigate the robot along a predefined path without the need for any additional external sensors. Meanwhile, the proposed approach combines various information using extend Kalman filter (EKF), include depth data from a pressure sensor, pose from an Inertial Measurement Unit (IMU), velocity from optical flow and pose estimation from multiple planar markers. A monocular downward facing camera is used to track feature about optical flow and detect artificial landmarks. Moreover, to validate our approach, we conducted experiment in an indoor pool with varying lighting and visibility conditions, and we demonstrate the online localization method is highly accurate, robust and successful application with limited computational capacities and low-cost sensing devices on our compact robot.
AB - Many techniques for robot localization rely on inertial navigation system which suffers from drift and huge computational cost. So, this paper presents a localization method which has a good real-time performance, high-precision and low-cost assumption for a compact amphibious spherical robot. Specifically, this system can navigate the robot along a predefined path without the need for any additional external sensors. Meanwhile, the proposed approach combines various information using extend Kalman filter (EKF), include depth data from a pressure sensor, pose from an Inertial Measurement Unit (IMU), velocity from optical flow and pose estimation from multiple planar markers. A monocular downward facing camera is used to track feature about optical flow and detect artificial landmarks. Moreover, to validate our approach, we conducted experiment in an indoor pool with varying lighting and visibility conditions, and we demonstrate the online localization method is highly accurate, robust and successful application with limited computational capacities and low-cost sensing devices on our compact robot.
KW - Amphibious Spherical Robot (ASR)
KW - Localization
KW - Sensor Fusion
UR - https://www.scopus.com/pages/publications/85072377766
U2 - 10.1109/ICMA.2019.8816345
DO - 10.1109/ICMA.2019.8816345
M3 - Conference contribution
AN - SCOPUS:85072377766
T3 - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
SP - 2523
EP - 2528
BT - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Mechatronics and Automation, ICMA 2019
Y2 - 4 August 2019 through 7 August 2019
ER -