DocumentCode :
2048303
Title :
3D localization and pose tracking system for an indoor Autonomous Mobile Robot
Author :
Juzhong Zhang ; Kai Zhao
Author_Institution :
4th Res. Dept., 713th Res. Inst., China Shipbuilding Ind. Corp., Zhengzhou, China
fYear :
2015
fDate :
2-5 Aug. 2015
Firstpage :
2209
Lastpage :
2214
Abstract :
This paper presents a new architecture that achieves 3D localization and pose tracking for an indoor Autonomous Mobile Robot (AMR). Specifically, for speeds of up to about 0.1m/s, the architecture could localize the position with an accuracy of 1.5 cm, and determine the orientation angle to within about 4 degrees error. The localization system consists of a microcontroller embedded in the AMR and five Wireless Sensor Nodes (WSN). Two ultrasonic transmitter nodes are attached to the AMR and three ultrasonic receiver nodes are fixed on a suspended bracket. Six ultrasonic time-of-flight (TOF) measurements are used to update the AMR´s pose by utilizing an Extended Kalman Filter (EKF) algorithm. In order to verify the concept, two experiment prototypes were built. In the first experiment, aiming at the precision of localization, orientation angle and slope angle, the AMR moves slowly along a slope. In the second experiment, focusing on the transient performance of the system when the orientation angle varies from one quadrant to another, the AMR moves along an arc. The results proved that the new architecture provides a high performance of localization and pose tracking for an AMR in an indoor environment.
Keywords :
Kalman filters; SLAM (robots); indoor environment; indoor navigation; mobile robots; pose estimation; ultrasonics; wireless sensor networks; 3D localization system; AMR; EKF algorithm; TOF measurement; WSN; extended Kalman filter; indoor autonomous mobile robot; pose tracking system; ultrasonic receiver node; ultrasonic time-of-flight measurement; wireless sensor node; Acoustics; Mobile communication; Mobile robots; Receivers; Robot sensing systems; Transmitters; Wireless sensor networks; Autonomous Mobile Robot; Kalman Filter; Localization; Wireless Sensor Node;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2015 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-7097-1
Type :
conf
DOI :
10.1109/ICMA.2015.7237829
Filename :
7237829
Link To Document :
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