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Design And Development Of Intelligent Navigation Control Systems For Autonomous Robots That Uses Neural Networks And Fuzzy Logic Techniques And Fpga For Its Implementation
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Book Synopsis Design and Development of Intelligent Navigation Control Systems for Autonomous Robots that Uses Neural Networks and Fuzzy Logic Techniques and FPGA for Its Implementation by : Christopher James Jeanniton
Download or read book Design and Development of Intelligent Navigation Control Systems for Autonomous Robots that Uses Neural Networks and Fuzzy Logic Techniques and FPGA for Its Implementation written by Christopher James Jeanniton and published by . This book was released on 2010 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Author's abstract: This research compares the behavior of three robot navigation controllers namely: PID, Artificial Neural Networks (ANN), and Fuzzy Logic (FL), that are used to control the same autonomous mobile robot platform navigating a real unknown indoor environment that contains simple geometric-shaped static objects to reach a goal in an unspecified location. In particular, the study presents and compares the design, simulation, hardware implementation, and testing of these controllers. The first controller is a traditional linear PID controller, and the other two are intelligent non-linear controllers, one using Artificial Neural Networks and the other using Fuzzy Logic Techniques. Each controller is simulated first in MATLAB® using the Simulink Toolbox. Later the controllers are implemented using Quartus ll® software and finally the hardware design of each controller is implemented and downloaded to a Field-Programmable Gate Array (FPGA) card which is mounted onto the mobile robot platform. The response of each controller was tested in the same physical testing environment using a maze that the robot should navigate avoiding obstacles and reaching the desired goal. To evaluate the controllers' behavior each trial run is graded with a standardized rubric based on the controllers' ability to react to situations presented within the trial run. The results of both the MATLAB® simulation and FPGA implementation show the two intelligent controllers, ANN and FL, outperformed the PID controller. The ANN controller was marginally superior to the FL controller in overall navigation and intelligence.
Book Synopsis Intelligent Mobile Robot Navigation by : Federico Cuesta
Download or read book Intelligent Mobile Robot Navigation written by Federico Cuesta and published by Springer Science & Business Media. This book was released on 2005-03-11 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Mobile Robot Navigation builds upon the application of fuzzy logic to the area of intelligent control of mobile robots. Reactive, planned, and teleoperated techniques are considered, leading to the development of novel fuzzy control systems for perception and navigation of nonholonomic autonomous vehicles. The unique feature of this monograph lies in its comprehensive treatment of the problem, from the theoretical development of the various schemes down to the real-time implementation of algorithms on mobile robot prototypes. As such, the book spans different domains ranging from mobile robots to intelligent transportation systems, from automatic control to artificial intelligence.
Book Synopsis Fuzzy Logic Techniques for Autonomous Vehicle Navigation by : Dimiter Driankov
Download or read book Fuzzy Logic Techniques for Autonomous Vehicle Navigation written by Dimiter Driankov and published by Physica. This book was released on 2010-10-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decade a critical mass of work that uses fuzzy logic for autonomous vehicle navigation has been reported. Unfortunately, reports of this work are scattered among conference, workshop, and journal publications that belong to different research communities (fuzzy logic, robotics, artificial intelligence, intelligent control) and it is therefore not easily accessible either to the new comer or to the specialist. As a result, researchers in this area may end up reinventing things while being unaware of important existing work. We believe that research and applications based on fuzzy logic in the field of autonomous vehicle navigation have now reached a sufficient level of maturity, and that it should be suitably reported to the largest possible group of interested practitioners, researches, and students. On these grounds, we have endeavored to collect some of the most representative pieces of work in one volume to be used as a reference. Our aim was to provide a volume which is more than "yet another random collection of papers," and gives the reader some added value with respect to the individual papers. In order to achieve this goal we have aimed at: • Selecting contributions which are representative of a wide range of prob lems and solutions and which have been validated on real robots; and • Setting the individual contributions in a clear framework, that identifies the main problems of autonomous robotics for which solutions based on fuzzy logic have been proposed.
Book Synopsis Recent Advances in Robotics and Automation by : Gourab Sen Gupta
Download or read book Recent Advances in Robotics and Automation written by Gourab Sen Gupta and published by Springer. This book was released on 2013-05-23 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: There isn’t a facet of human life that has not been touched and influenced by robots and automation. What makes robots and machines versatile is their computational intelligence. While modern intelligent sensors and powerful hardware capabilities have given a huge fillip to the growth of intelligent machines, the progress in the development of algorithms for smart interaction, collaboration and pro-activeness will result in the next quantum jump. This book deals with the recent advancements in design methodologies, algorithms and implementation techniques to incorporate intelligence in robots and automation systems. Several articles deal with navigation, localization and mapping of mobile robots, a problem that engineers and researchers are grappling with all the time. Fuzzy logic, neural networks and neuro-fuzzy based techniques for real world applications have been detailed in a few articles. This edited volume is targeted to present the latest state-of-the-art computational intelligence techniques in Robotics and Automation. It is a compilation of the extended versions of the very best papers selected from the many that were presented at the 5th International Conference on Automation, Robotics and Applications (ICARA 2011) which was held in Wellington, New Zealand from 6-8 December, 2011. Scientists and engineers who work with robots and automation systems will find this book very useful and stimulating.
Book Synopsis Vision Based Autonomous Robot Navigation by : Amitava Chatterjee
Download or read book Vision Based Autonomous Robot Navigation written by Amitava Chatterjee and published by Springer. This book was released on 2012-10-13 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is devoted to the theory and development of autonomous navigation of mobile robots using computer vision based sensing mechanism. The conventional robot navigation systems, utilizing traditional sensors like ultrasonic, IR, GPS, laser sensors etc., suffer several drawbacks related to either the physical limitations of the sensor or incur high cost. Vision sensing has emerged as a popular alternative where cameras can be used to reduce the overall cost, maintaining high degree of intelligence, flexibility and robustness. This book includes a detailed description of several new approaches for real life vision based autonomous navigation algorithms and SLAM. It presents the concept of how subgoal based goal-driven navigation can be carried out using vision sensing. The development concept of vision based robots for path/line tracking using fuzzy logic is presented, as well as how a low-cost robot can be indigenously developed in the laboratory with microcontroller based sensor systems. The book describes successful implementation of integration of low-cost, external peripherals, with off-the-shelf procured robots. An important highlight of the book is that it presents a detailed, step-by-step sample demonstration of how vision-based navigation modules can be actually implemented in real life, under 32-bit Windows environment. The book also discusses the concept of implementing vision based SLAM employing a two camera based system.
Book Synopsis Autonomous Vehicle Navigation by : Lounis Adouane
Download or read book Autonomous Vehicle Navigation written by Lounis Adouane and published by CRC Press. This book was released on 2016-04-21 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improve the Safety, Flexibility, and Reliability of Autonomous Navigation in Complex EnvironmentsAutonomous Vehicle Navigation: From Behavioral to Hybrid Multi-Controller Architectures explores the use of multi-controller architectures in fully autonomous robot navigation-even in highly dynamic and cluttered environments. Accessible to researchers
Book Synopsis Vision-Based Mobile Robot Control and Path Planning Algorithms in Obstacle Environments Using Type-2 Fuzzy Logic by : Mahmut Dirik
Download or read book Vision-Based Mobile Robot Control and Path Planning Algorithms in Obstacle Environments Using Type-2 Fuzzy Logic written by Mahmut Dirik and published by Springer Nature. This book was released on 2021-03-01 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book includes topics, such as: path planning, avoiding obstacles, following the path, go-to-goal control, localization, and visual-based motion control. The theoretical concepts are illustrated with a developed control architecture with soft computing and artificial intelligence methods. The proposed vision-based motion control strategy involves three stages. The first stage consists of the overhead camera calibration and the configuration of the working environment. The second stage consists of a path planning strategy using several traditional path planning algorithms and proposed planning algorithm. The third stage consists of the path tracking process using previously developed Gauss and Decision Tree control approaches and the proposed Type-1 and Type-2 controllers. Two kinematic structures are utilized to acquire the input values of controllers. These are Triangle Shape-Based Controller Design, which was previously developed and Distance-Based Triangle Structure that is used for the first time in conducted experiments. Four different control algorithms, Type-1 fuzzy logic, Type-2 Fuzzy Logic, Decision Tree Control, and Gaussian Control have been used in overall system design. The developed system includes several modules that simplify characterizing the motion control of the robot and ensure that it maintains a safe distance without colliding with any obstacles on the way to the target. The topics of the book are extremely relevant in many areas of research, as well as in education in courses in computer science, electrical and mechanical engineering and in mathematics at the graduate and undergraduate levels.
Book Synopsis Development and Application of Fuzzy Logic-based Autonomous Robot Navigation Algorithms by : Xiaoyu Yang
Download or read book Development and Application of Fuzzy Logic-based Autonomous Robot Navigation Algorithms written by Xiaoyu Yang and published by . This book was released on 2005 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy logic is a logical system which is much closer to human thinking and natural language than traditional logical systems. Furthermore, fuzzy logic is capable of expressing and manipulating imprecise, vague, and ill-defined quantities in a systematic manner. These features make it possible to use fuzzy logic in autonomous navigation algorithms for mobile robots. The resulting fuzzy logic-based navigation algorithms can endow a robot with the ability of emulating humanoid behavior when coping with a large amount of uncertainty in real-world environments. Based on the observation of the behavior of human beings in dynamic environments, three fuzzy autonomous robot navigation algorithms are proposed in this thesis. The direction-based fuzzy reactive algorithm combines information about obstacles and the goal position together and gives the final steering direction which is safe, in the sense of avoiding collisions, and desired, in the sense of seeking the goal. The fuzzy-Braitenberg navigation strategy takes advantage of the essential characteristics of a differential drive robot and combines fuzzy logic with the ideas of Braitenberg vehicles, taking into account obstacle repulsion and goal attraction to set the speeds for the motors. In the layered goal-oriented fuzzy motion planning algorithm, information about the global goal and the long-range sensory data are used by the first layer of the planner to produce an intermediate goal, referred to as the way-point, that gives a favorable direction in terms of seeking the goal within the detected area. The second layer of the planner takes this way-point as a subgoal and, using short-range sensory data, guides the robot to reach the subgoal while avoiding collisions. Systematic procedures of the design and implementation of the three algorithms are addressed. The resulting navigation algorithms are implemented on a real mobile robot, the Koala, and extensively tested in various environments. Experimental results are presented which demonstrate the effectiveness and success of the proposed fuzzy navigation systems.
Book Synopsis Robot Navigation from Nature by : Michael John Milford
Download or read book Robot Navigation from Nature written by Michael John Milford and published by Springer Science & Business Media. This book was released on 2008-02-11 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This pioneering book describes the development of a robot mapping and navigation system inspired by models of the neural mechanisms underlying spatial navigation in the rodent hippocampus. Computational models of animal navigation systems have traditionally had limited performance when implemented on robots. This is the first research to test existing models of rodent spatial mapping and navigation on robots in large, challenging, real world environments.
Book Synopsis Multi-model Intelligent Controller Based on Neural Networks and Fuzzy Logic by : Mohammad Adnan Mohammad Al-Akhras
Download or read book Multi-model Intelligent Controller Based on Neural Networks and Fuzzy Logic written by Mohammad Adnan Mohammad Al-Akhras and published by . This book was released on 1997 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: An important problem within the majority of controllers is to accommodate disturbances. The disturbance normally shifts the process away from the desired trajectory which results in performance degradation. Therefore a controller has to be designed to drive the process back to its required performance specifications. The multi-model control scheme, is a technique that depends on multiple representations of the process, using different models at various operating points, and on the desired trajectory. The control scheme must first locate the model which best represents the process, and then, this model is used to generate the control signal needed to drive the process to follow the desired trajectory. The main problem of this approach is the possibly large number of models required to represent the process and hence much computation may be required. In this thesis, intelligent control schemes are proposed, based on the multi-model technique, where only two models are needed to represent the process over the entire operating conditions. Various approaches are used to develop the intelligent controller, namely, the multilayer neural network which was trained using the backpropagation algorithm and genetic algorithms, the radial basis function neural network, fuzzy logic, and the neuro-fuzzy logic approach. The intelligent controller has been first implemented using a multilayer neural network that was trained to force the system to follow the desired response. Then it was implemented by a radial basis function neural network to explore its potential. The fuzzy logic technique has also been explored to develop a fuzzy logic controller based on input-output observation of the system variables. Then, the fuzzy logic concept is implemented using the multilayer neural network and its learning mechanism, to develop a neuro-fuzzy controller, which combines the advantages of both. The performance of these controllers has been investigated on different types of systems to show the effectiveness of their applicability.
Book Synopsis Advanced Intelligent Control in Robots by : Luige Vladareanu
Download or read book Advanced Intelligent Control in Robots written by Luige Vladareanu and published by Mdpi AG. This book was released on 2023-07-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advanced intelligent control is a rapidly developing, complex and challenging field with significant practical importance and potential applications. The authors aim to stimulate advancements in science and technology by addressing this field and presenting new trends in the design, control and applications of real-time intelligent sensor system control using advanced intelligent control methods and techniques. The purpose of the Special Issue is to promote in-depth research and communication regarding these topics. The authors focus on innovative multi-sensor fusion techniques integrated into robots, which are combined with computer vision, virtual and augmented reality (VR&AR) and intelligent communication including remote control, adaptive sensor networks and human-robot (H2R) interaction systems. Special attention is given to advancements in sensors, actuators, computation technology and communication networks that provide the necessary tools for implementing intelligent control hardware. These advancements are targeted toward various scientific research fields, including machine learning (such as deep learning), bio-inspired algorithms, recurrent neural networks, neuro-fuzzy control and artificial intelligence in general. The Special Issue includes original research papers that report on the recent advancements in intelligent control using intelligent sensors. It serves as a further extension of the previously successful Special Issue, "Advanced Intelligent Control through Versatile Intelligent Portable Platforms".
Book Synopsis Sensor Modelling, Design And Data Processing For Autonomous Navigation by : Martin David Adams
Download or read book Sensor Modelling, Design And Data Processing For Autonomous Navigation written by Martin David Adams and published by World Scientific. This book was released on 1999-02-04 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This invaluable book presents an unbiased framework for modelling and using sensors to aid mobile robot navigation. It addresses the problem of accurate and reliable sensing in confined environments and makes a detailed analysis of the design and construction of a low cost optical range finder. This is followed by a quantitative model for determining the sources and propagation of noise within the sensor. The physics behind the causes of erroneous data is also used to derive a model for detecting and labelling such data as false. In addition, the author's data-processing algorithms are applied to the problem of environmental feature extraction. This forms the basis of a solution to the problem of mobile robot localisation. The book develops a relationship between the kinematics of a mobile robot during the execution of successive manoeuvres, and the sensed features. Results which update a mobile vehicle's position using features from 2D and 3D scans are presented.
Book Synopsis The optimization of intelligent control interfaces using Versatile Intelligent Portable Robot Platform by : Victor Vladareanu
Download or read book The optimization of intelligent control interfaces using Versatile Intelligent Portable Robot Platform written by Victor Vladareanu and published by Infinite Study. This book was released on with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper presents a VIPRO versatile, intelligent and mobile platform for robots, using an original virtual projection method which involves the representation of modern mobile robots in a 3D virtual environment using a strong robotic simulator, an open architecture system and adaptive networks over the classical control system of the robot, developing intelligent control interfaces The advanced control technologies adapted to the robot environment such as neutrosophic control, robot Extenics control and robot haptic control are used.
Book Synopsis Mobile Robot Navigation Using a Vision Based Approach by : Mehmet Serdar Güzel
Download or read book Mobile Robot Navigation Using a Vision Based Approach written by Mehmet Serdar Güzel and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This study addresses the issue of vision based mobile robot navigation in a partially cluttered indoor environment using a mapless navigation strategy. The work focuses on two key problems, namely vision based obstacle avoidance and vision based reactive navigation strategy. The estimation of optical flow plays a key role in vision based obstacle avoidance problems, however the current view is that this technique is too sensitive to noise and distortion under real conditions. Accordingly, practical applications in real time robotics remain scarce. This dissertation presents a novel methodology for vision based obstacle avoidance, using a hybrid architecture. This integrates an appearance-based obstacle detection method into an optical flow architecture based upon a behavioural control strategy that includes a new arbitration module. This enhances the overall performance of conventional optical flow based navigation systems, enabling a robot to successfully move around without experiencing collisions. Behaviour based approaches have become the dominant methodologies for designing control strategies for robot navigation. Two different behaviour based navigation architectures have been proposed for the second problem, using monocular vision as the primary sensor and equipped with a 2-D range finder. Both utilize an accelerated version of the Scale Invariant Feature Transform (SIFT) algorithm. The first architecture employs a qualitative-based control algorithm to steer the robot towards a goal whilst avoiding obstacles, whereas the second employs an intelligent control framework. This allows the components of soft computing to be integrated into the proposed SIFT-based navigation architecture, conserving the same set of behaviours and system structure of the previously defined architecture. The intelligent framework incorporates a novel distance estimation technique using the scale parameters obtained from the SIFT algorithm. The technique employs scale parameters and a corresponding zooming factor as inputs to train a neural network which results in the determination of physical distance. Furthermore a fuzzy controller is designed and integrated into this framework so as to estimate linear velocity, and a neural network based solution is adopted to estimate the steering direction of the robot. As a result, this intelligent iv approach allows the robot to successfully complete its task in a smooth and robust manner without experiencing collision. MS Robotics Studio software was used to simulate the systems, and a modified Pioneer 3-DX mobile robot was used for real-time implementation. Several realistic scenarios were developed and comprehensive experiments conducted to evaluate the performance of the proposed navigation systems. KEY WORDS: Mobile robot navigation using vision, Mapless navigation, Mobile robot architecture, Distance estimation, Vision for obstacle avoidance, Scale Invariant Feature Transforms, Intelligent framework.
Book Synopsis Development of an Intelligent Navigation Algorithm for Mobile Robots Using Fuzzy Logic Techniques by : Steven D. Drews
Download or read book Development of an Intelligent Navigation Algorithm for Mobile Robots Using Fuzzy Logic Techniques written by Steven D. Drews and published by . This book was released on 1999 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Navigation and Coordination of Autonomous Mobile Robots with Limited Resources by : Matthew D. Knudson
Download or read book Navigation and Coordination of Autonomous Mobile Robots with Limited Resources written by Matthew D. Knudson and published by . This book was released on 2010 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of autonomous robots in complex exploration tasks is rapidly increasing. Indeed, robots can provide speed and cost effectiveness in many tasks, as well as allow operation in environments that are hostile to humans. In this dissertation we: 1) provide two adaptive navigation algorithms; 2) develop a coordination mechanism; 3) develop a dynamic partnership formation mechanism; and 4) demonstrate the use of algorithms in a hardware implementation. The two adaptive navigation algorithms are neuro-evolution and policy gradient, where the results show that effective, adaptive navigation techniques can be developed for mobile robots in an exploration domain when the robots have limited capabilities. In addition, we show that policy gradient approaches thrive on short-term objective values, whereas neuro-evolutionary approaches provide more robust results with a time-extended objective value. Finally, we show that summing short-term values to generate a time-extended value does not capture the complexities of some real world exploration tasks. Coordinating multi-robot systems to maximize global information collection in these exploration domains presents additional challenges. In particular, in many multi-robot domains where communication is expensive, the coordination must be achieved in a passive manner. This is done in this dissertation via objective design on a hierarchical control scheme where both a navigation algorithm and coordination algorithm are operating simultaneously. We then extend results on such multi-robot coordination algorithms to domains where the robots cannot achieve the required tasks without forming teams. We investigate team formation where: i) robots must perform a task together; ii) there is an optimal number of robots; and iii) individuals vary, forming heterogeneous teams. The results show that using neuro-evolutionary robot teams with objective functions that are aligned with the global objective and locally computable significantly improve over robots using the global objective directly, particularly in dynamic environments. Finally, we develop a path to implementation of all of the coordination research done to date into robot hardware. The design represents a stable, robust robotic platform on which navigation and coordination algorithms can be run in the fashion they were developed and intricacies of real-world operation can be analyzed. Functional experiments show that the platform operates as expected and performs similarly to algorithm work done in simulation.
Book Synopsis Vision Based Robot Navigation by : Muhammad Amar
Download or read book Vision Based Robot Navigation written by Muhammad Amar and published by LAP Lambert Academic Publishing. This book was released on 2013 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aspiration of this research work is to design vision based intelligent mobile robot navigation techniques to capacitate an autonomous robot to navigate in indoor/outdoor environments. The images from mobile robot, accoutered with a camera, are preprocessed and are used for drivable region extraction. A novel weighted matrix algorithm (WMA) is used for drivable region division for, both, constructed and unconstructed scenarios. Hurdle distance, reckoned from ultrasonic sensors information, is used in conjunction with extracted drivable road to generate the motion commands for road following and hurdle avoidance behavior. Navigation controller design has been actualized in MATLAB by exerting fuzzy logic soft computing techniques to engender the sought motion commands. The designed controllers are evaluated in a simulator for assorted hurdle and environment conditions prior to real time implementation on archetype robot.
