Abstract
This paper presents a Kinect sensor-based control approach for two humanoid robot hands. Firstly, the D-H method is used to establish forward and inverse kinematics models for the humanoid robot hands, establish the 3D models of the humanoid robot hands by 3ds Max, and prove the correctness of the kinematics models by simulations. Secondly, the depth images and the bone joint point information are used to segment the operator’s hand gesture from the depth images. Finally, the operator’s hand gestures are recognized by DBN, which are converted into a series of instructions to control the humanoid robot hands on time. The experimental results show that recognition accuracy rate is high and can meet the real time requirements.
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Acknowledgments
This research is funded by the National Natural Science Foundation (Project No. 61573145), the Public Research and Capacity Building of Guangdong Province (Project No. 2014B010104001) and the Basic and Applied Basic Research of Guang-dong Province (Project No. 2015A030308018), the authors are greatly thanks to these grants.
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Hu, B., Xiao, Nf. (2018). Kinect Sensor-Based Motion Control for Humanoid Robot Hands. In: Qiao, F., Patnaik, S., Wang, J. (eds) Recent Developments in Mechatronics and Intelligent Robotics. ICMIR 2017. Advances in Intelligent Systems and Computing, vol 690. Springer, Cham. https://doi.org/10.1007/978-3-319-65978-7_81
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DOI: https://doi.org/10.1007/978-3-319-65978-7_81
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