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Orchestration of Robotic Platform and Implementation of Adaptive Self-Learning Neuro-Fuzzy Controller

Rameez Raja Chowdhary, Manju K. Chattopadhyay, Raj Kamal

Abstract


Abstract

The paper presents design, development and implementation of a robotic platform based on orchestration model. An orchestration model helps the user to reuse the services and provide easy porting from robot to robot with reduced project development time. Orchestration of Robotic Platform (ORP) is simple and based on open source Arduino architecture. The hardware of platform consists of sensors, actuators and Arduino board. The software deploys orchestration-programming model. An Adaptive Self-learning Neuro-fuzzy Controller (ASLNFC) is also designed and implemented, for testing the robots in real-time environment. The ASLNFC uses structure and parameter learning methods for performance enhancement of robot. A collision avoidance task is also included. The results of our real-time experiments show the effectiveness of ASLNFC and usability of ORP.

 

Keywords: Robotic Platform, orchestration, neuro-fuzzy controller, networks, collision avoidance

Cite this Article

Rameez Raja Chowdhary, Manju K. Chattopadhyay, Raj Kamal. Orchestration of Robotic Platform and Implementation of Adaptive Self-Learning Neuro-Fuzzy Controller. Journal of Electronic Design Technology. 2017; 8(3): 17–29p.


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