Designing a robot to follow a command from the analysis of the image received from the operator
محورهای موضوعی : فصلنامه شبیه سازی و تحلیل تکنولوژی های نوین در مهندسی مکانیک
Majid Amiri
1
(Department of Mechanical Engineering, University of Malek-e-Ashtar, Isfahan, Iran)
Shayan Farokhi Aleh Kouhi
2
(Department of Mechanical Engineering, University of Shahid Mohajer, Isfahan, Iran.)
Ahmad Keshavarzi
3
(Department of Mechanical Engineering, Khomeinishahr Branch, Islamic Azad University, Isfahan, Iran)
کلید واژه: MATLAB, Robot, Digital image processing, hand gesture recognition,
چکیده مقاله :
In the beginning, to use robots, a person must be next to them to be able to use them. Therefore, it is necessary to design a robot that can be operated without a person physically present. This article is about the operation of a robot that is not near us and can be launched from a control station. This is possible through a technique called image processing. In order to simplify an acceptable solution for a user-friendly interface, commands can be applied to a wireless robot using hand gestures. Will be the motion detection system includes three stages of image capture, feature extraction, and algorithm decision making. When the gesture is detected, a command signal is generated and sent to the micro-controllers. These command signals are then sent to the robot to make it run in a certain direction. One of the applications of the robot is to select and replace cases where human intervention is not possible. The pick and place arm is a microcontroller-based mechatronic system that selects the object from the source location and places it in a desired location, this operation is controlled using a keyboard. In addition, the robot records video signals with its RF camera at 2.4GHz (installed on the robot). The live video of the robot is received at the base station (computer). It is tested in the MAT software and the video is simultaneously processed in the DSP code.
[1] Ahmed, T. (2012). A neural network based real time hand gesture recognition system. International journal of computer applications, 59(4).
[2] Dhawan, A., & Honrao, V. (2013). Implementation of hand detection based techniques for human computer interaction. arXiv preprint arXiv:1312.7560.
[3] Kaura, H. K., Honrao, V., Patil, S., & Shetty, P. (2013). Gesture controlled robot using image processing. International Journal of Advanced Research in Artificial Intelligence, 2(5).
[4] Jain, M., Aditi, A. L., Khan, M. F., & Maurya, A. (2012). Wireless gesture control robot: an analysis. International Journal of Advanced Research in Computer and Communication Engineering, 1(10), 855-857.
[5] Swetha, N. (2013). Design and implementation of accelerometer based robot motion and speed control with obstacle detection. Int. J. Sci. Eng. Technol, 2, 749-755.
[6] MaruthiSagar, N. V., Kumar, D. S., & Geethanjali, N. (2014). MEMS based gesture controlled robot using wireless communication. International Journal of Engineering Trends and Technology, 14(4), 185-188.
[7] Khan, R. Z., & Ibraheem, N. A. (2012). Hand gesture recognition: a literature review. International journal of artificial Intelligence & Applications, 3(4), 161.
[8] Malima, Ozgur, & Cetin. (2006). A fast algorithm for vision-based hand gesture recognition for robot control. 2006 IEEE 14th Signal Processing and Communications Applications, 1-4.
