@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00210330,
 author = {Hiroshi, Nakahara and Kittikhun, Thongpull and Hiroshi, Nakahara and Kittikhun, Thongpull},
 book = {Proceedings of Asia Pacific Conference on Robot IoT System Development and Platform},
 month = {Mar},
 note = {In this work, an automatic robotic manipulator control based on visual information for object tracking is presented. The tracking process employ Recurrent Neural Network technique to predict the location of target object which is used to calculate movement of the robot. We also propose an object analysis based on image processing technique for object width estimation. We implemented the proposed system with an actual robotic manipulator with a gripper for experiments. The experiments shown that object size estimation method results the maximum accuracy at 1.13% and the tacking process can effectively keep the target object in the position suitable to perform grasp., In this work, an automatic robotic manipulator control based on visual information for object tracking is presented. The tracking process employ Recurrent Neural Network technique to predict the location of target object which is used to calculate movement of the robot. We also propose an object analysis based on image processing technique for object width estimation. We implemented the proposed system with an actual robotic manipulator with a gripper for experiments. The experiments shown that object size estimation method results the maximum accuracy at 1.13% and the tacking process can effectively keep the target object in the position suitable to perform grasp.},
 pages = {67--68},
 publisher = {情報処理学会},
 title = {A development of visual-feedback automatic control for robotic manipulator},
 volume = {2020},
 year = {2021}
}