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Obstacle Avoidance in Multi-robot Systems

Obstacle Avoidance in Multi-robot Systems
Author: Mark A. C. Gill
Publisher: World Scientific
Total Pages: 202
Release: 1998
Genre: Technology & Engineering
ISBN: 9789810234232

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Obstacle Avoidance in Multi-robot Systems: Experiments in Parallel Genetic Algorithms offers a novel framework for solving the path planning problem for robot manipulators. Simple and efficient solutions are proposed for the path planning problem based on genetic algorithms. One of the attractive features of genetic algorithms is their ability to solve formidable problems in a robust and straightforward manner. Moreover, genetic algorithms are inherently parallel in nature, which makes them ideal candidates for parallel computing implementations.By combining the robustness of genetic algorithms with the power of parallel computers, this book provides an effective and practical approach to solving path planning problems. The book gives details of implementations that allow a better understanding of the complexities involved in the development of parallel path planning algorithms. The material presented is interdisciplinary in nature ? it combines topics from robotics, genetic algorithms, and parallel processing. The book can be used by practitioners and researchers in computer science and engineering.


Evolutionary Robotics: From Algorithms To Implementations

Evolutionary Robotics: From Algorithms To Implementations
Author: Ling-feng Wang
Publisher: World Scientific
Total Pages: 267
Release: 2006-07-17
Genre: Technology & Engineering
ISBN: 9814477524

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This invaluable book comprehensively describes evolutionary robotics and computational intelligence, and how different computational intelligence techniques are applied to robotic system design. It embraces the most widely used evolutionary approaches with their merits and drawbacks, presents some related experiments for robotic behavior evolution and the results achieved, and shows promising future research directions. Clarity of explanation is emphasized such that a modest knowledge of basic evolutionary computation, digital circuits and engineering design will suffice for a thorough understanding of the material.The book is ideally suited to computer scientists, practitioners and researchers keen on computational intelligence techniques, especially the evolutionary algorithms in autonomous robotics at both the hardware and software levels.


Odour Detection by Mobile Robots

Odour Detection by Mobile Robots
Author: R. Andrew Russell
Publisher: World Scientific
Total Pages: 236
Release: 1999
Genre: Science
ISBN: 9789810237912

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Insects are extremely successful creatures, thriving in our ever-changing & unpredictable world. One of the factors behind their success is the use of odour to increase their efficiency when searching for food, to help navigate between a source of food & their nest & to enable them to find a mate. Mobile robots would have their capabilities greatly enhanced if they could make use of similar techniques. This important book describes current research aimed at giving robots the ability to generate, detect & discriminate between odours, together with the control algorithms using such sensory information. Contents: Chemical Sensing in Nature; Odour-Sensing Technology; Odour Discrimination; Airflow; Broadcast Chemical Signals; Chemical Markings as Signals; Trail Following; Coding Information into Trails; Heat as a Short-Lived Marker. Readership: Graduate students & researchers in robotics, mechatronics & artificial intelligence.


Adaptive Neural Network Control of Robotic Manipulators

Adaptive Neural Network Control of Robotic Manipulators
Author: Tong Heng Lee
Publisher: World Scientific
Total Pages: 400
Release: 1998
Genre:
ISBN: 9789810234522

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Introduction; Mathematical background; Dynamic modelling of robots; Structured network modelling of robots; Adaptive neural network control of robots; Neural network model reference adaptive control; Flexible joint robots; task space and force control; Bibliography; Computer simulation; Simulation software in C.


Interdisciplinary Approaches To Robot Learning

Interdisciplinary Approaches To Robot Learning
Author: Andreas Birk
Publisher: World Scientific
Total Pages: 220
Release: 2000-06-12
Genre: Technology & Engineering
ISBN: 9814492973

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Robots are being used in increasingly complicated and demanding tasks, often in environments that are complex or even hostile. Underwater, space and volcano exploration are just some of the activities that robots are taking part in, mainly because the environments that are being explored are dangerous for humans. Robots can also inhabit dynamic environments, for example to operate among humans, not just in factories, but also taking on more active roles. Recently, for instance, they have made their way into the home entertainment market. Given the variety of situations that robots will be placed in, learning becomes increasingly important.Robot learning is essentially about equipping robots with the capacity to improve their behaviour over time, based on their incoming experiences. The papers in this volume present a variety of techniques. Each paper provides a mini-introduction to a subfield of robot learning. Some also give a fine introduction to the field of robot learning as a whole. There is one unifying aspect to the work reported in the book, namely its interdisciplinary nature, especially in the combination of robotics, computer science and biology. This approach has two important benefits: first, the study of learning in biological systems can provide robot learning scientists and engineers with valuable insights into learning mechanisms of proven functionality and versatility; second, computational models of learning in biological systems, and their implementation in simulated agents and robots, can provide researchers of biological systems with a powerful platform for the development and testing of learning theories.


High-level Feedback Control With Neural Networks

High-level Feedback Control With Neural Networks
Author: Young Ho Kim
Publisher: World Scientific
Total Pages: 228
Release: 1998-09-28
Genre: Technology & Engineering
ISBN: 9814496456

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Complex industrial or robotic systems with uncertainty and disturbances are difficult to control. As system uncertainty or performance requirements increase, it becomes necessary to augment traditional feedback controllers with additional feedback loops that effectively “add intelligence” to the system. Some theories of artificial intelligence (AI) are now showing how complex machine systems should mimic human cognitive and biological processes to improve their capabilities for dealing with uncertainty.This book bridges the gap between feedback control and AI. It provides design techniques for “high-level” neural-network feedback-control topologies that contain servo-level feedback-control loops as well as AI decision and training at the higher levels. Several advanced feedback topologies containing neural networks are presented, including “dynamic output feedback”, “reinforcement learning” and “optimal design”, as well as a “fuzzy-logic reinforcement” controller. The control topologies are intuitive, yet are derived using sound mathematical principles where proofs of stability are given so that closed-loop performance can be relied upon in using these control systems. Computer-simulation examples are given to illustrate the performance.


Sensor Modelling, Design and Data Processing for Autonomous Navigation

Sensor Modelling, Design and Data Processing for Autonomous Navigation
Author: Martin David Adams
Publisher: World Scientific
Total Pages: 260
Release: 1999
Genre: Technology & Engineering
ISBN: 9789810234966

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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.


Fuzzy Logic Control: Advances In Applications

Fuzzy Logic Control: Advances In Applications
Author: Robert Babuska
Publisher: World Scientific
Total Pages: 341
Release: 1999-03-19
Genre: Technology & Engineering
ISBN: 9814495158

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Fuzzy logic control has become an important methodology in control engineering. This volume deals with applications of fuzzy logic control in various domains. The contributions are divided into three parts. The first part consists of two state-of-the-art tutorials on fuzzy control and fuzzy modeling. Surveys of advanced methodologies are included in the second part. These surveys address fuzzy decision making and control, fault detection, isolation and diagnosis, complexity reduction in fuzzy systems and neuro-fuzzy methods. The third part contains application-oriented contributions from various fields, such as process industry, cement and ceramics, vehicle control and traffic management, electromechanical and production systems, avionics, biotechnology and medical applications. The book is intended for researchers both from the academic world and from industry.


Scheduling in Parallel Computing Systems

Scheduling in Parallel Computing Systems
Author: Shaharuddin Salleh
Publisher: Springer Science & Business Media
Total Pages: 177
Release: 2012-12-06
Genre: Computers
ISBN: 1461550653

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Scheduling in Parallel Computing Systems: Fuzzy and Annealing Techniques advocates the viability of using fuzzy and annealing methods in solving scheduling problems for parallel computing systems. The book proposes new techniques for both static and dynamic scheduling, using emerging paradigms that are inspired by natural phenomena such as fuzzy logic, mean-field annealing, and simulated annealing. Systems that are designed using such techniques are often referred to in the literature as `intelligent' because of their capability to adapt to sudden changes in their environments. Moreover, most of these changes cannot be anticipated in advance or included in the original design of the system. Scheduling in Parallel Computing Systems: Fuzzy and Annealing Techniques provides results that prove such approaches can become viable alternatives to orthodox solutions to the scheduling problem, which are mostly based on heuristics. Although heuristics are robust and reliable when solving certain instances of the scheduling problem, they do not perform well when one needs to obtain solutions to general forms of the scheduling problem. On the other hand, techniques inspired by natural phenomena have been successfully applied for solving a wide range of combinatorial optimization problems (e.g. traveling salesman, graph partitioning). The success of these methods motivated their use in this book to solve scheduling problems that are known to be formidable combinatorial problems. Scheduling in Parallel Computing Systems: Fuzzy and Annealing Techniques is an excellent reference and may be used for advanced courses on the topic.


Search and Classification Using Multiple Autonomous Vehicles

Search and Classification Using Multiple Autonomous Vehicles
Author: Yue Wang
Publisher: Springer Science & Business Media
Total Pages: 167
Release: 2012-04-02
Genre: Technology & Engineering
ISBN: 1447129563

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Search and Classification Using Multiple Autonomous Vehicles provides a comprehensive study of decision-making strategies for domain search and object classification using multiple autonomous vehicles (MAV) under both deterministic and probabilistic frameworks. It serves as a first discussion of the problem of effective resource allocation using MAV with sensing limitations, i.e., for search and classification missions over large-scale domains, or when there are far more objects to be found and classified than there are autonomous vehicles available. Under such scenarios, search and classification compete for limited sensing resources. This is because search requires vehicle mobility while classification restricts the vehicles to the vicinity of any objects found. The authors develop decision-making strategies to choose between these competing tasks and vehicle-motion-control laws to achieve the proposed management scheme. Deterministic Lyapunov-based, probabilistic Bayesian-based, and risk-based decision-making strategies and sensor-management schemes are created in sequence. Modeling and analysis include rigorous mathematical proofs of the proposed theorems and the practical consideration of limited sensing resources and observation costs. A survey of the well-developed coverage control problem is also provided as a foundation of search algorithms within the overall decision-making strategies. Applications in both underwater sampling and space-situational awareness are investigated in detail. The control strategies proposed in each chapter are followed by illustrative simulation results and analysis. Academic researchers and graduate students from aerospace, robotics, mechanical or electrical engineering backgrounds interested in multi-agent coordination and control, in detection and estimation or in Bayes filtration will find this text of interest.