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Analysis and Review of Average Fuzzy Inference Technique and Other AI Techniques Used for Robot Control and Navigation

Parhi Dayal R
2020 Current Trends in Computer Sciences & Applications  
Using the Average Fuzzy Inference technique robot navigates from start position to goal position avoiding obstacles while reaching the target. The simulation results agree with experimental results.  ...  In this paper application of average fuzzy inference technique has been analysed for navigation control of robotic agent.  ...  Mohanty PK, Parhi DR (2014) Navigation of autonomous mobile robot using adaptive network based fuzzy inference system.  ... 
doi:10.32474/ctcsa.2020.02.000129 fatcat:za5nrkcvxjeyfdf5nf6fvjsoyy

Development of Novel Average Neuro Fuzzy Hybrid Control Technique for Robot Navigation in Unknown Environments

2020 Advances in Machine Learning & Artificial Intelligence  
The current research focuses on development and analysis of novel Average Neuro-Fuzzy Controller for path planning and navigation of mobile robot in highly cluttered environment.  ...  Using the sensors reading robots negotiate with the obstacles present in the environments during navigation from start to goal point.  ...  International Journal of Fuzzy Systems 4. Parhi DR, Mohanty PK (2012) A Study of various 22 :1314-1329. methodologies used for navigation of autonomous mobile 17.  ... 
doi:10.33140/amlai.01.01.08 fatcat:vwtchiqlxrcudczoct5npa6xty

PATH FINDING BASED ON ARTIFICIAL INTELLIGENCE TECHNIQUES: A REVIEW

Dr. Eyad I. Abbas, Dr. Sundus D. Hasan, Rawaa Jawad
2020 International Journal of Engineering Applied Sciences and Technology  
The survey shows GA (genetic algorithm), PSO (particle swarm optimization), Neuro -fuzzy, fuzzy, ACO, from this review of this study finding a researcher used ANFIS, Fuzzy major used for path finding for  ...  mobile robot.  ...  Abu Baker, [44] has described how we can get a navigation system by shunning obstacles using the hybrid Neuro-Fuzzy algorithm.  ... 
doi:10.33564/ijeast.2020.v05i04.013 fatcat:6ayyqxh5enbrplfunh5vkx2vva

Versatile Intelligent Portable Robot Platform Developed through Adaptive Neuro-Fuzzy Control

Luige Vladareanu, Romanian Academy, Institute of Solid Mechanics, Romanian, Victor Vladareanu, Hongbo Wang, Yongfei Feng, Mihai Radulescu, Alexandra-Catalina Ciocîrlan
2019 International Journal of Modeling and Optimization  
It was developed an intelligent control interfaces that apply advanced control technologies adapted to the robot environment such as control by artificial intelligence techniques using adaptive neuro-fuzzy  ...  The Cartesian robot workspace, which is learned using an adaptive neuro-fuzzy control for the prediction of desired references was generate.  ...  ADAPTIVE NEURO-FUZZY CONTROL INTERFACES WITH REHABILITATION ROBOTS APPLICATIONS Fuzzy logic is widely used worldwide as a landmark of artificial intelligence.  ... 
doi:10.7763/ijmo.2019.v9.722 fatcat:tdnvamuyl5btfg6ux4tza7nhya

Adaptive Position Tracking System and Force Control Strategy for Mobile Robot Manipulators Using Fuzzy Wavelet Neural Networks

Mai Thang Long, Wang Yao Nan
2014 Journal of Intelligent and Robotic Systems  
In this paper, we propose an adaptive position tracking system and a force control strategy for nonholonomic mobile robot manipulators, which incorporate the merits of Fuzzy Wavelet Neural Networks (FWNNs  ...  The design of adaptive online learning algorithms is derived using M. T. Long ( ) · Lyapunov stability theorem.  ...  Adaptive control based on neural networks (NNs) is also a useful method to deal with the unknown/uncertain dynamics of the mobile robot manipulators system.  ... 
doi:10.1007/s10846-013-0006-5 fatcat:wsmmq35k5bblfjkzgneoxwkgwu

Tipover Stability Enhancement Of Wheeled Mobile Manipulators Using An Adaptive Neuro- Fuzzy Inference Controller System

A. Ghaffari, A. Meghdari, D. Naderi, S. Eslami
2008 Zenodo  
In this paper an algorithm based on the adaptive neuro-fuzzy controller is provided to enhance the tipover stability of mobile manipulators when they are subjected to predefined trajectories for the end-effector  ...  base, rule bases are designed for the ANFIS controller and will be exerted on the actuators to enhance the tipover stability of the mobile manipulator.  ...  Intelligent mobile manipulator navigation using adaptive neuro-fuzzy systems is considered in [15] .  ... 
doi:10.5281/zenodo.1076185 fatcat:cnenvhnm6ngbdnjcpqbapx5phu

Research Trends on Fuzzy Logic Controller for Mobile Robot Navigation: A Scientometric Study

Somiya Rani, Amita Jain, Oscar Castillo
2020 Journal of Automation, Mobile Robotics & Intelligent Systems  
The present study shows the scientometric analysis of the publications on the fuzzy logic controller in autonomous mobile robot navigation during the period 2000 to 2018.  ...  Ma, "Intelligent mobile manipulator nav- igation using adaptive neuro-fuzzy systems", Information Sciences, vol. 171, no. 4, 2005, 447-474, DOI: 10.1016/j.ins.2004.09.014. [61] J. Z.  ...  Parhi, "Navigation of mul- tiple mobile robots in a highly clutter terrains using adaptive neuro-fuzzy inference system", Robotics and Autonomous Systems, vol. 72, 2015, 48-58, DOI: 10.1016/j.robot  ... 
doi:10.14313/jamris/1-2020/11 fatcat:thyoitic7vd5bg6rqnjwjea6qa

Mobile Robot Feature-Based SLAM Behavior Learning, and Navigation in Complex Spaces [chapter]

Ebrahim A. Mattar
2018 Applications of Mobile Robots [Working Title]  
To achieve this, the mobile system was built on diverse levels of intelligence, this includes principle component analysis (PCA), neuro-fuzzy (NF) learning system as a classifier, and fuzzy rule based  ...  Mobile intelligence has been based on blending a number of functionaries related to navigation, including learning SLAM map main features.  ...  In terms of leaning intelligent navigation, intelligent robot control using an adaptive critic with a task control center and dynamic database was also introduced by Hall et al. [16] .  ... 
doi:10.5772/intechopen.81195 fatcat:w4qvcalwera5rd7efa2rkjv5qy

Intelligent learning and control of autonomous robotic agents operating in unstructured environments

Hani Hagras, Tarek Sobh
2002 Information Sciences  
Intelligence helps because it gives systems the capacity to adapt more rapidly to environmental changes or to handle much more complex functions.  ...  Because environments and users of systems continuously change, robotic agents have to be adaptive.  ...  Fukuda, presents an effective generation method of adjustment strategies for a fuzzy-neuro force controller (FNFC) of a robot manipulator in an unknown environment.  ... 
doi:10.1016/s0020-0255(02)00221-9 fatcat:ul5wno4oonhvphivc3257pkgqa

2019 Index IEEE Transactions on Cognitive and Developmental Systems Vol. 11

2019 IEEE Transactions on Cognitive and Developmental Systems  
., +, TCDS June 2019 188-199 Fuzzy neural networks Combined Sensing, Cognition, Learning, and Control for Developing Future Neuro-Robotics Systems: A Survey.  ...  Liu, H., +, TCDS June 2019 176-187 Adaptive Behavior Acquisition of a Robot Based on Affective Feedback and Combined Sensing, Cognition, Learning, and Control for Developing Future Neuro-Robotics Systems  ... 
doi:10.1109/tcds.2020.2967228 fatcat:6holx3xlrjdjnf5nedahp4fl6m

Design and Simulation of Anfis Controller for Virtual-Reality-Built Manipulator [chapter]

Yousif I. Al Mashhadany
2012 Fuzzy Controllers- Recent Advances in Theory and Applications  
Hui et al. and Rusu et al. discuss neuro-fuzzy controllers for sensor-based mobile robot navigation.  ...  Garbi et al. implemented an adaptive neuro-fuzzy inference system in robotic vehicle navigation [24] [25] [26] . Robots are one way to improve industrial automation productivity.  ... 
doi:10.5772/48383 fatcat:3dfheqlh4zcuzafcaux6u35lcy

Virtual and intelligent traffic signs in rescue simulation system: Imitation of human society in agent society

Mostafa Asghari, Behrooz Masoumi, Mohammad Reza Meybodi
2009 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA)  
This system ...expand Applying a neuro-fuzzy classifier for gesture-based control using a single wrist- proposes a theoretical approach of gainscheduled fuzzy PI control design based on gain and phase  ...  during the navigation mission of autonomous mobile robots.  ...  SECTION: Fuzzy logic New fuzzy-based anti-swing controller for helicopter slung-load system near hover Hanafy M.  ... 
doi:10.1109/cira.2009.5423206 dblp:conf/cira/AsghariMM09 fatcat:r5aq3mrpuvd7zdnf3ju7rflzrq

The Review of Soft Computing Applications in Humanitarian Demining Robots Design

Mehdi Neshat, Ghodrat Sepidname, Elnaz Mehri, Amin Zalimoghadam
2016 Indian Journal of Science and Technology  
Using different methods such as Neural Network, Fuzzy Logic, Fuzzy Neural Network or other soft computing methods have been able to render the behaviors of these robots more intelligent, more precise,  ...  Findings: The advancement of the demining robot along with its becoming more intelligent is of particular importance, so that they would be able to carry out their operations autonomously and adaptively  ...  A hexapod robot is designed in this research and a Neuro-fuzzy adaptive controller is used for controlling and coordinating joint movements ( Figure 10 ) 31 .  ... 
doi:10.17485/ijst/2016/v9i4/55595 fatcat:hehn3iua2rgoddc6wtumflehgq

An Algorithm Based on Neuro-Fuzzy Controller Implemented in A Smart Clothing System For Obstacle Avoidance

Senem Kursun Bahadir, Sebastien Thomassey, Vladan Koncar, Fatma Kalaoglu
2013 International Journal of Computational Intelligence Systems  
In their system, they used neuro-fuzzy environment.  ...  and sonar based area mapping and navigation by (1998). Navigation strategy of an intelligent mobile mobile robots. 7th IEEE International Conference robot using fuzzy logic.  ... 
doi:10.1080/18756891.2013.781336 fatcat:gdhr26lvtnhgngabvt5t3jbo44

Robust Hybrid Intelligent Based Motion Control of Industrial Robot Manipulators for Unstructured Dynamic Environment

M Dev Anand, N Ramasamy
2019 Sun International Journal of Engineering and Basic Sciences  
Neuro fuzzy systems are excellent in determining the input and output relationships using a simple data. The traditional fuzzy logic system is replaced with the back propagation neural network.  ...  This is possible only with neuro fuzzy techniques since several of its controllers are trained using simple data received from human control of robotic arm and this study quantifies and compares their  ...  Ding and Li (1999) , used fuzzy logic system to solve obstacle problem for a redundant manipulator.  ... 
doi:10.30558/ijebs.20190202001 fatcat:wv3lv7annbcg5mjzobv2d5zfwq
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