TY - GEN
T1 - A real-time monocular tracking method for low-cost mobile robot
AU - Ren, Ruonan
AU - Chen, Guangzeng
AU - Wang, Mingliang
AU - Lou, Yunjiang
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/8
Y1 - 2018/8
N2 - Moving object locating and tracking are always the challenges in computer vision, especially in autonomous mobile robot vision. Due to the relative movement between the object and the robot as well as the image overexposure, the images are easily got blur, or worse, the object is loss and unable to be tracked. High-performance hardware and complex intelligent algorithms can make up these abuses in some degree, however, these solutions are of high cost and unable to be realized in consumer robots. Addressing on this problem, an improved Apriltag-based tracking algorithm running on a low cost embedded mobile robot with Raspberry Pi3 is proposed. Dynamic downsampling algorithm is first proposed to improve the real-time performance of the traditional Apriltag-based tracking algorithm. The dynamic downsampling coefficient is then studied through experiments and fitting technology. Then the relative velocity is also taken into account to enhance the downsampling accuracy. Image enhancement based on histogram equalization is used to reduce the image blur caused by downsampling and the relative motion. Finally, a secondary detection algothm is designed based on Apriltag's recognition principle to improve the locating and tracking rate.
AB - Moving object locating and tracking are always the challenges in computer vision, especially in autonomous mobile robot vision. Due to the relative movement between the object and the robot as well as the image overexposure, the images are easily got blur, or worse, the object is loss and unable to be tracked. High-performance hardware and complex intelligent algorithms can make up these abuses in some degree, however, these solutions are of high cost and unable to be realized in consumer robots. Addressing on this problem, an improved Apriltag-based tracking algorithm running on a low cost embedded mobile robot with Raspberry Pi3 is proposed. Dynamic downsampling algorithm is first proposed to improve the real-time performance of the traditional Apriltag-based tracking algorithm. The dynamic downsampling coefficient is then studied through experiments and fitting technology. Then the relative velocity is also taken into account to enhance the downsampling accuracy. Image enhancement based on histogram equalization is used to reduce the image blur caused by downsampling and the relative motion. Finally, a secondary detection algothm is designed based on Apriltag's recognition principle to improve the locating and tracking rate.
UR - https://www.scopus.com/pages/publications/85072321738
U2 - 10.1109/ICInfA.2018.8812466
DO - 10.1109/ICInfA.2018.8812466
M3 - 会议稿件
AN - SCOPUS:85072321738
T3 - 2018 IEEE International Conference on Information and Automation, ICIA 2018
SP - 917
EP - 922
BT - 2018 IEEE International Conference on Information and Automation, ICIA 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Information and Automation, ICIA 2018
Y2 - 11 August 2018 through 13 August 2018
ER -