Abstract
Currently the development of robots has reached a high level of complexity. However, it is also accompanied by increasing complexity problems in its control. Some control with the image processing method also requires competent operators, at least memorize each command used. Therefore, to reduce the complexity in its control, in this research robot control, especially humanoid robot is made using motion capture method. Motion capture is a control technique using a camera transducer in the form of Microsoft Kinect, to obtain the coordinate skeleton of the joint user. Furthermore the data is processed in Visual Studio software to obtain the angular information that will be formed by the robot. So that the robot can perform the same movement with the user. The information is transmitted wirelessly to the microcontroller contained on the robot in real-time. The results of research showed that the system can translate the user's movement into information movement of humanoid robot. With an average skeleton vector detection error of 1.69 cm, an average response time of 1.3 seconds and an absolute error average position of the end effector on the x axis of 3.2 cm and on the y-axis of 1.28 cm.
Highlights
The use of robots in the present has blended into all aspects of everyday life
Deepan at SASTRA University in 2015 uses a camera for tracking human fingers and recognizing gestures based on color and contour changes, and by counting the distance from the midpoint of the palm to the tip of each finger [2], Another study conducted at Al-Nahrain University is already using Microsoft Kinect transducer [3]
Users serve as a set point that produces movement, the movement of the user will be read as a skeleton data which in-tracking by Microsoft Kinect device
Summary
The use of robots in the present has blended into all aspects of everyday life. Because with the robot, various human activities can be helped so that more effective and efficient, they are usually called service robot. Comes the more recent method of control, namely by using a camera that serves as a transducer producing gesture data used to drive the humanoid robot. Some research on humanoid robot control using image processing has been done, but most transducers used are web-cam to generate RGB image data or by using 2 cameras (stereo vision). Deepan at SASTRA University in 2015 uses a camera for tracking human fingers and recognizing gestures based on color and contour changes, and by counting the distance from the midpoint of the palm to the tip of each finger [2], Another study conducted at Al-Nahrain University is already using Microsoft Kinect transducer [3]. From the background are formulated several problems, including: Human / human readout process using Microsoft Kinect transducer into gesture skeleton data. Human movement can be detected and imitated in real-time by humanoid robot, with the limitation of movement according to the specification of the robot
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