Abstract
Autonomous grasping of manipulator is a challenging problem, due to the difficulties and accuracy of object recognition and localization. This paper presents a binocular vision-based approach, which enables to recognize and locate object accurately with a binocular. This approach, which is based on the limitation of the application of the traditional manipulator, aims to achieve autonomous grasp of manipulator. The main contribution of this paper is to construct the recognition and localization system. Firstly, the left camera of the binocular is used to collect the image information, and the TensorFlow is used to imply the ResNet to build the recognition system; Then the principle of the ranging of the binocular is used for locating the target object; Finally, tests have been performed in three different indoor environments to achieve autonomous grasping of manipulator. The proposed object recognition and localization approach is testified by successfully autonomous grasping of manipulator, and experimental results show that the accuracy reaches 89.83% averagely.
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Duan, R., Li, S., Yuan, Z., Zhang, Y. (2019). Object Recognition and Localization Base on Binocular Vision. In: Wang, Y., Huang, Q., Peng, Y. (eds) Image and Graphics Technologies and Applications. IGTA 2019. Communications in Computer and Information Science, vol 1043. Springer, Singapore. https://doi.org/10.1007/978-981-13-9917-6_29
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DOI: https://doi.org/10.1007/978-981-13-9917-6_29
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