TY - GEN
T1 - Depth estimation of objects with known geometric model for IBVS using an eye-in-hand camera
AU - Wu, Ju Feng
AU - Cheng, Ming Yang
N1 - Funding Information:
ACKNOWLEDGMENT The authors would like to thank the Ministry of Science and Technology, Taiwan, for support of this research under Grant Nos. NSC 101-2221-E-006-185 and MOST 103-2221-E-006-185-MY2.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - One of the most crucial and challenging issues in Image-Based Visual Servoing (IBVS) is the derivation of accurate depth information of feature points, which is indispensable in the calculation of the image Jacobian. For an object without a known geometric model, it is difficult to retrieve the depth information of feature points using a single camera. However, in many application scenarios such as industrial manufacturing processes, geometric models of artificial objects such as polyhedrons are known in advance. As a result, this paper aims at developing an estimation algorithm that can be used to retrieve the depth information of an object with a known geometric model. Several computer simulations and real experiments have been conducted to verify the effectiveness of the proposed depth estimation algorithm. In addition, a 6-DOF industrial robot is used to perform an eye-in-hand IBVS task with the aid of the proposed depth estimation algorithm.
AB - One of the most crucial and challenging issues in Image-Based Visual Servoing (IBVS) is the derivation of accurate depth information of feature points, which is indispensable in the calculation of the image Jacobian. For an object without a known geometric model, it is difficult to retrieve the depth information of feature points using a single camera. However, in many application scenarios such as industrial manufacturing processes, geometric models of artificial objects such as polyhedrons are known in advance. As a result, this paper aims at developing an estimation algorithm that can be used to retrieve the depth information of an object with a known geometric model. Several computer simulations and real experiments have been conducted to verify the effectiveness of the proposed depth estimation algorithm. In addition, a 6-DOF industrial robot is used to perform an eye-in-hand IBVS task with the aid of the proposed depth estimation algorithm.
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U2 - 10.1109/ARIS.2017.8297195
DO - 10.1109/ARIS.2017.8297195
M3 - Conference contribution
AN - SCOPUS:85054303473
SN - 9781538624197
T3 - International Conference on Advanced Robotics and Intelligent Systems, ARIS
BT - 2017 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2017
Y2 - 6 September 2017 through 8 September 2017
ER -