DESIGN AND IMPLEMENTATION OF WIRELESS VOICE CONTROLLED MOBILE ROBOT
AbstractThis paper presents a technique for a speech recognizer used to control the motion of an intelligent automated mobile robot. The aim is to interact with the mobile robot using natural and direct communication techniques. The voice is processed to get proper and safe movement of a mobile robot and satisfying high recognition rate. Features are extracted from speech signal using Mel Frequency Cepstral Coefficients (MFCC). To realize feature matching, an efficient Dynamic Time Warping (DTW)-based speech recognition system is presented which is applicable for isolated words of Arabic language. The tested words are compared to a trained database using this DTW algorithm. On the other side, the mobile robot is designed with two servo motors as driving actuators. These actuators are controlled by L298 motor driver circuit. The control algorithm is programmed and downloaded into a PIC18F45K22 microcontroller which is interfaced to a USB port of a 10" notebook computer. The robot proves a capability of understanding the full meaning of the five Arabic speech commands that steer it forward, backward, right, left, or stop.
Alkhouli M., 1990, Alaswaat Alaghawaiyah, Dar Alfalah, Amman, Jordan, (Arabic reference).
Al-Zabibi M., 1990, An acoustic-phonetic approach in automatic Arabic speech recognition, The British Library in Association with UMI, UK.
Jean-Marc V., Shun’ichi Y., Jean R., Francois M., Kazuhiro N., and Hiroshi G., 2007, Robust recognition of simultaneous speech by a mobile robot, IEEE Transactions on Robotics, Vol.23, No.4. P. 742-752.
Khalid A.D., Ala F., Iyad F., Baraa A., and Saed W., 2013, Efficient DTW-Based speech recognition system for isolated words of Arabic language, World Academy of Science, Engineering and Technology, Vol. 7, P. 106-113, Iraq.
Lindasalwa M., Mumtaj Begam and I. Elamvazuthi, 2010, Voice recognition algorithms using Mel frequency cepstral coefficient (MFCC) and dynamic time warping (DTW) techniques, Journal of Computing, Vol.2, issue 3, ISSN 2151-9617.
Microchip Technology Inc., 2012, Low power, high performance microcontrollers.
Plannerer B., 2005, An Introduction to speech recognition, Bernd Plannerer, Munich, Germany.
Que D., Jian Yang ; Bo Wei ; Hui Li ; Zhihong Jiang ; Danfeng Li ; Hongjie Li ; Qiang Huang, 2011, A method on trajectory plan for humanoid space robot , Robotics and Biomimetic (ROBIO), IEEE International Conference, P. 281-286. Thailand.
Rachna J., and Saxena S., 2011, Voice automated mobile robot, International Journal of Computer Applications (0975-8887), Vol. 16, No. 2, India.
Rover 5, available at: https://www.sparkfun.com/products/10336
Shivanker D., Geeta N., and Poonam P., 2007, Isolated speech recognition using MFCC and DTW, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol.2, Issue 8, 2013, ISO 3297: certified organization, India.
User's Guide, 2012, L298 dual H-bridge motor driver.
User's Manual, 2012, MicroC: C compiler for Microchip PIC microcontrollers, Mikroelektronika, Belgrade.
User's Guide, 2013, EasyPIC7", Mikroelectronika, Belgrade.
Yoshioka, T. ; Shimada, N. ; Ohishi, K. ; Miyazaki, T. ; Yokokura, Y., 2014, Link-coupled vibration suppression control considering product of inertia for industrial robots, Advanced Motion Control (AMC), IEEE 13th International Workshop, P. 675 – 680, Yokohama, Japan.
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