Navigation Control of a Mobile Robot under Time Constraint using Genetic Algorithms, CSP Techniques, and Fuzzy Logic

2016 ◽  
pp. 932-954
Author(s):  
Tlijani Hayet ◽  
Tlijani Hatem ◽  
Knani Jilani
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Time Delay ◽  
Mobile Robot ◽  
Constraint Satisfaction ◽  
Current Velocity ◽  
Fuzzy Controller ◽  
Time Window ◽  
Constraint Satisfaction Problem ◽  
Navigation Control

This chapter proposes a two-input-and-one-output fuzzy controller for a two-wheeled mobile robot. The robot moves following a hybrid plan based on Genetic Algorithms and Constraint Satisfaction Problem techniques. The path yielded by this hybrid plan is structured by artificial beacons. In each position of these beacons, the current velocity of the controlled robot is by itself an input for the fuzzy controller. The second input is the time delay between the current position and the next sub goal to be reached. The proposed fuzzy controller aims to converge the time delay between positions in the path tracking closely to a time window. It gives the appropriate acceleration so that the time delay becomes closer to the time window.

Navigation Control of a Mobile Robot under Time Constraint using Genetic Algorithms, CSP Techniques, and Fuzzy Logic

2015 ◽  
pp. 457-478
Author(s):  
Tlijani Hayet ◽  
Tlijani Hatem ◽  
Knani Jilani
Keyword(s):  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Time Delay ◽  
Mobile Robot ◽  
Constraint Satisfaction ◽  
Current Velocity ◽  
Fuzzy Controller ◽  
Time Window ◽  
Constraint Satisfaction Problem ◽  
Navigation Control

This chapter proposes a two-input-and-one-output fuzzy controller for a two-wheeled mobile robot. The robot moves following a hybrid plan based on Genetic Algorithms and Constraint Satisfaction Problem techniques. The path yielded by this hybrid plan is structured by artificial beacons. In each position of these beacons, the current velocity of the controlled robot is by itself an input for the fuzzy controller. The second input is the time delay between the current position and the next sub goal to be reached. The proposed fuzzy controller aims to converge the time delay between positions in the path tracking closely to a time window. It gives the appropriate acceleration so that the time delay becomes closer to the time window.

Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

2019 ◽  
Vol 20 (1) ◽  
pp. 51-62
Author(s):  
Rajmeet Singh ◽  
Tarun Kumar Bera
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Bond Graph ◽  
Membership Functions ◽  
Current Position ◽  
Dc Motors

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

Neural network and fuzzy logic techniques based collision avoidance for a mobile robot

Robotica ◽  
1997 ◽  
Vol 15 (6) ◽  
pp. 627-632 ◽  
Author(s):  
Minglu Zhang ◽  
Shangxian Peng ◽  
Qinghao Meng
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Mobile Robot ◽  
Fuzzy Controller ◽  
Perceptual Space ◽  
Space Partitioning ◽  
Reactive Navigation ◽  
3 Dimensional ◽  
Sensory Data ◽  
Cluttered Environment

This paper is concerned with a mobile robot reactive navigation in an unknown cluttered environment based on neural network and fuzzy logic. Reactive navigation is a mapping between sensory data and commands without planning. This article's task is to provide a steering command letting a mobile robot avoid a collision with obstacles. In this paper, the authors explain how to perform a currently perceptual space partitioning for a mobile robot by the use of an ART neural network, and then, how to build a 3-dimensional fuzzy controller for mobile robot reactive navigation. The results presented, whether experimented or simulation, show that our method is well adapted to this type of problem.

scholarly journals Navigation control of mobile robot using interval type-2 neural fuzzy controller optimized by dynamic group differential evolution

2018 ◽  
Vol 10 (1) ◽  
pp. 168781401775248 ◽  
Author(s):  
Tzu-Chao Lin ◽  
Chao-Chun Chen ◽  
Cheng-Jian Lin
Keyword(s):  
Mobile Robot ◽  
Differential Evolution ◽  
Fuzzy Controller ◽  
Dynamic Group ◽  
Unknown Environments ◽  
Navigation Control ◽  
Interval Type ◽  
Wall Following ◽  
Neural Fuzzy

This study developed and effectively implemented an efficient navigation control of a mobile robot in unknown environments. The proposed navigation control method consists of mode manager, wall-following mode, and towards-goal mode. The interval type-2 neural fuzzy controller optimized by the dynamic group differential evolution is exploited for reinforcement learning to develop an adaptive wall-following controller. The wall-following performance of the robot is evaluated by a proposed fitness function. The mode manager switches to the proper mode according to the relation between the mobile robot and the environment, and an escape mechanism is added to prevent the robot falling into the dead cycle. The experimental results of wall-following show that dynamic group differential evolution is superior to other methods. In addition, the navigation control results further show that the moving track of proposed model is better than other methods and it successfully completes the navigation control in unknown environments.

Machine vision and fuzzy logic-based navigation control of a goal-oriented mobile robot

2016 ◽  
Vol 24 (3) ◽  
pp. 168-180 ◽  
Author(s):  
Panus Nattharith ◽  
Mehmet Serdar Güzel
Keyword(s):  
Fuzzy Logic ◽  
Machine Vision ◽  
Mobile Robot ◽  
Navigation Control

Selected Papers from HNICEM 2007

2008 ◽  
Vol 12 (4) ◽  
pp. 327-327
Author(s):  
Elmer P. Dadios ◽  
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Real Time ◽  
Fuzzy Controller ◽  
Sliding Mode ◽  
Optimal Path ◽  
Image Processing Technique ◽  
Special Issue ◽  
International Conference ◽  
The Third

The Third International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) was held in Century Park Hotel, Manila, Philippines from March 15 to 18, 2007. The theme on this conference was Technology Creativity and Innovations for Economic Development. As has been done from the previous HNICEM conferences, cutting edge papers presented from this conference are reviewed and selected for JACIII special issue publication. In this special issue, 10 articles are selected that will provide valuable references for researchers and practitioners. The first article presents an integrated algorithm that provides a mobile robot the ability to plan an optimal path and does online collision avoidance in a totally unknown environment. The second article presents a fuzzy controller technique in navigation with obstacle avoidance for a general purpose mobile robot in a given global environment with image processing technique using Open Source Computer Vision. The third article presents a model-based controller for helicopter using the sliding mode approach. The controller assumes that only measured outputs are available and it uses sliding mode observer to estimate the state of the system. The fourth article presents a real-time fuzzy logic based parallel parking system in an FPGA platform. The fifth article presents performance analysis of container unloading operations using simplified analytical model (SAM). The sixth article presents a neuro-fuzzy approach with additional moving average window data filter and fuzzy clustering algorithm use to forecast electrical load. The seventh article presents a new design and implementation of a multi-output fuzzy controller for real time control which utilizes lesser memory and executes faster than an existing type of multiple single-output fuzzy logic controllers. The eight article presents a new method based on multi-objective evolutionary algorithms to evolve low complexity neural controllers that allows an agent to perform two different tasks simultaneously. The ninth and tenth articles present genetic networks programming for stock market trading rules and for traffic systems applications, respectively. We extend our warmest thanks and deepest gratitude to the distinguished authors and reviewers who have contributed to this special issue for their outstanding contributions and cooperation. We are also grateful to Prof. Toshio Fukuda and Prof. Kaoru Hirota, chief editors of JACIII, for their continued support to all the HINICEM International Conferences. Come March 12 to 15, 2009, the 4th HNICEM International Conference will be held in Manila, Philippines. We thank the IEEE Philippines for its continuing sponsorship. Also to JACIII journal, as outstanding papers presented in this conference will be selected for publication in a special issue. We invite you to submit your research papers and to participate in HNICEM 2009. For further information, please visit “http://www.dlsu.edu.ph/conferences/hnicem/”.

scholarly journals Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Hajer Omrane ◽  
Mohamed Slim Masmoudi ◽  
Mohamed Masmoudi
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Fuzzy Controller ◽  
Mobile Robot Navigation ◽  
Infrared Range ◽  
Indoor Environments ◽  
Autonomous Mobile Robot ◽  
Ir Sensors ◽  
Navigation Algorithms ◽  
Trajectory Tracking Controller

This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation and obstacle avoidance. The used mobile robot is equipped with DC motor, nine infrared range (IR) sensors to measure the distance to obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent navigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform. Simulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path.

Formalising PFSQL queries using ŁΠ fuzzy logic

2011 ◽  
Vol 22 (3) ◽  
pp. 533-547 ◽  
Author(s):  
ALEKSANDAR PEROVIĆ ◽  
ALEKSANDAR TAKAČI ◽  
SRDJAN ŠKRBIĆ
Keyword(s):  
Fuzzy Logic ◽  
Constraint Satisfaction ◽  
Relational Databases ◽  
Query Language ◽  
Constraint Satisfaction Problem ◽  
Current Paper ◽  
Conservative Extension ◽  
Logic Formula ◽  
Structured Query Language

Using the concept of a generalised priority constraint satisfaction problem, we previously found a way to introduce priority queries into fuzzy relational databases. The results were PFSQL (Priority Fuzzy Structured Query Language) together with a database independent interpreter for it. In an effort to improve the performance of the resolution of PFSQL queries, the aim of the current paper is to formalise PFSQL queries by obtaining their interpretation in an existing fuzzy logic. We have found that the ŁΠ logic provides sufficient elements. The SELECT line of PFSQL queries is semantically a formula of some fuzzy logic, and we show that such formulas can be naturally expressed in a conservative extension of the ŁΠ logic. Furthermore, we prove a theorem that gives the PSPACE containment for the complexity of finding a model for a given ŁΠ logic formula.

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