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This book starts with an introduction to robots and robotics. Forward and inverse kinematics problems of serial manipulators have been dealt in details. After discussing trajectory planning schemes, inverse dynamics problem of serial manipulator has been solved. A separate chapter has been devoted to the analysis of wheeled robot. It then concentrates on analysis of two-legged robot. The working principles of different types of sensors used in robots have been explained in one chapter. Various steps involved in robot vision have then been discussed in detail. The last chapter deals with different motion planning schemes of robots. It has been written to fulfill the requirements of a large number of readers belonging to various disciplines of engineering. It will be very much helpful to the students, scientists and practicing engineers.
SOFT COMPUTING: Fundamentals and Applications starts with an introduction to soft computing, a family consists of many members, namely Genetic Algorithms (GAs), Fuzzy Logic (FL), Neural Networks (NNs), and others. To realize the need for a non-traditional optimization tool like GA, one chapter is devoted to explain the principle of traditional optimization. The working cycle of a GA is explained in detail. The mechanisms of some specialized GAs are then discussed with some appropriate examples. The working principles of some other non-traditional optimization tools like Simulated Annealing (SA) and Particle Swarm Optimization (PSO) are discussed in detail. Multi-objective optimization has be...
Soft Computing starts with an introduction to soft computing, a family consists of many members, namely genetic algorithms (GAs), fuzzy logic (FL), neural networks (NNs), and others. To realize the need for a non-traditional optimization tool like GA, one chapter is devoted to explain the principle of traditional optimization. The working cycle of a GA is explained in detail. The mechanisms of some specialized GAs are then discussed with some appropriate examples. The working principles of some other non-traditional optimization tools like simulated annealing (SA) and particle swarm optimization (PSO) are discussed in detail. Multi-objective optimization has been dealt in a separate chapter,...
This research book contains a sample of most recent research in the area of intelligent autonomous systems. The contributions include: General aspects of intelligent autonomous systems Design of intelligent autonomous robots Biped robots Robot for stair-case navigation Ensemble learning for multi-source information fusion Intelligent autonomous systems in psychiatry Condition monitoring of internal combustion engine Security management of an enterprise network High dimensional neural nets and applications This book is directed to engineers, scientists, professor and the undergraduate/postgraduate students who wish to explore this field further.
This book describes the development of an integrated approach for generating the path and gait of realistic hexapod robotic systems. It discusses in detail locomation with straight-ahead, crab and turning motion capabilities in varying terrains, like sloping surfaces, staircases, and various user-defined rough terrains. It also presents computer simulations and validation using Virtual Prototyping (VP) tools and real-world experiments. The book also explores improving solutions by applying the developed nonlinear, constrained inverse dynamics model of the system formulated as a coupled dynamical problem based on the Newton–Euler (NE) approach and taking into account realistic environmental conditions. The approach is developed on the basis of rigid multi-body modelling and the concept that there is no change in the configuration of the system in the short time span of collisions.
Nature-inspired computation is an interdisciplinary topic area that connects the natural sciences to computer science. Since natural computing is utilized in a variety of disciplines, it is imperative to research its capabilities in solving optimization issues. The Handbook of Research on Natural Computing for Optimization Problems discusses nascent optimization procedures in nature-inspired computation and the innovative tools and techniques being utilized in the field. Highlighting empirical research and best practices concerning various optimization issues, this publication is a comprehensive reference for researchers, academicians, students, scientists, and technology developers interested in a multidisciplinary perspective on natural computational systems.
This volume is based on the proceedings of the 28th International Conference on CAD/CAM, Robotics and Factories of the Future. This book specially focuses on the positive changes made in the field of robotics, CAD/CAM and future outlook for emerging manufacturing units. Some of the important topics discussed in the conference are product development and sustainability, modeling and simulation, automation, robotics and handling systems, supply chain management and logistics, advanced manufacturing processes, human aspects in engineering activities, emerging scenarios in engineering education and training. The contents of this set of proceedings will prove useful to both researchers and practitioners.
This book highlights the recent research on hybrid intelligent systems and their various practical applications. It presents 58 selected papers from the 20th International Conference on Hybrid Intelligent Systems (HIS 2020) and 20 papers from the 12th World Congress on Nature and Biologically Inspired Computing (NaBIC 2020), which was held online, from December 14 to 16, 2020. A premier conference in the field of artificial intelligence, HIS - NaBIC 2020 brought together researchers, engineers and practitioners whose work involves intelligent systems, network security and their applications in industry. Including contributions by authors from 25 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of science and engineering.
This edited volume deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business and commerce. It comprises 15 chapters including an introductory chapter which covers the fundamental definitions and outlines some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
Pattern Recognition has a long history of applications to data analysis in business, military and social economic activities. While the aim of pattern recognition is to discover the pattern of a data set, the size of the data set is closely related to the methodology one adopts for analysis. Intelligent Data Analysis: Developing New Methodologies Through Pattern Discovery and Recovery tackles those data sets and covers a variety of issues in relation to intelligent data analysis so that patterns from frequent or rare events in spatial or temporal spaces can be revealed. This book brings together current research, results, problems, and applications from both theoretical and practical approaches.