DESIGN OF A TRAINABLE CONTROLLER INSPIRED FROM NEURAL SYSTEM TO GENERATE COMPLEX BEHAVIORS IN HUMANOID ROBOTS

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PARANDEH REYHANEH; SHAHBAZI HAMED; JAMSHIDI KAMAL; KHODABANDEH JAHROMI BEHNAM

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Journal: Modares Mechanical Engineering Year:2016 | Volume:16 | Issue:2 Page(s): 59-68

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Information Journal Paper

Title

DESIGN OF A TRAINABLE CONTROLLER INSPIRED FROM NEURAL SYSTEM TO GENERATE COMPLEX BEHAVIORS IN HUMANOID ROBOTS

Author(s)

PARANDEH REYHANEH | SHAHBAZI HAMED | JAMSHIDI KAMAL | KHODABANDEH JAHROMI BEHNAM | Issue Writer Certificate

Keywords

HUMANOID ROBOTQ1

NEURAL NETWORKQ2

CONTROLQ2

IMITATION LEARNINGQ1

Abstract

In this paper a new method for motion CONTROL in HUMANOID ROBOTs has been introduced. The problem of movement learning, especially dance and repetitive actions of human beings to HUMANOID ROBOTs is a major challenge in the field of robotics. IMITATION LEARNING, which is a subset of supervised learning, is one of the main forms used to teach complex tasks to the HUMANOID ROBOT, and is, accordingly based on the concept that an artificial system can imitate a great deal of information through learning from a human trainer. The main technique uses Central Pattern Generators structures which are able to produce required motion trajectories based on IMITATION LEARNING. Systematic design of these NEURAL NETWORKs is the main problem that is solved in this paper. The proposed model is a basic paradigm for IMITATION LEARNING in the HUMANOID ROBOTs which do not require direct design of CONTROLler and programming. The proposed model has many benefits including smooth walking patterns and modulation during imitation.Simulation results of this learning system in the robot simulator (WEBOTS) have been linked with MATLAB software and its implementation on a NAO robot demonstrates that the robot has learned the desired motion with high accuracy. This model can be extended and used in the Nao soccer player both for the standard platform and the 3D soccer simulation leagues of Robocup SPL competitions to train different types of motions.

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APA: Copy

PARANDEH, REYHANEH, SHAHBAZI, HAMED, JAMSHIDI, KAMAL, & KHODABANDEH JAHROMI, BEHNAM. (2016). DESIGN OF A TRAINABLE CONTROLLER INSPIRED FROM NEURAL SYSTEM TO GENERATE COMPLEX BEHAVIORS IN HUMANOID ROBOTS. MODARES MECHANICAL ENGINEERING, 16(2), 59-68. SID. https://sid.ir/paper/178825/en

Vancouver: Copy

PARANDEH REYHANEH, SHAHBAZI HAMED, JAMSHIDI KAMAL, KHODABANDEH JAHROMI BEHNAM. DESIGN OF A TRAINABLE CONTROLLER INSPIRED FROM NEURAL SYSTEM TO GENERATE COMPLEX BEHAVIORS IN HUMANOID ROBOTS. MODARES MECHANICAL ENGINEERING[Internet]. 2016;16(2):59-68. Available from: https://sid.ir/paper/178825/en

IEEE: Copy

REYHANEH PARANDEH, HAMED SHAHBAZI, KAMAL JAMSHIDI, and BEHNAM KHODABANDEH JAHROMI, “DESIGN OF A TRAINABLE CONTROLLER INSPIRED FROM NEURAL SYSTEM TO GENERATE COMPLEX BEHAVIORS IN HUMANOID ROBOTS,” MODARES MECHANICAL ENGINEERING, vol. 16, no. 2, pp. 59–68, 2016, [Online]. Available: https://sid.ir/paper/178825/en

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