Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that integrates literature from several fields into a coherent source for teaching and reference in applications including robotics, computational biology, computer graphics, manufacturing, aerospace applications, and medicine.

Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. Written for computer scientists and engineers with interests in artificial intelligence, robotics, or control theory, this is the only book on this topic that tightly integrates a vast body of literature from several fields into a coherent source for teaching and reference in a wide variety of applications. Difficult mathematical material is explained through hundreds of examples and illustrations.

A state-of-the-art survey that reports on the progress made in selected areas of this important and growing field, aiding the analysis of existing networks and the design of new and more efficient algorithms for solving various problems on these networks.

This book presents extensive research on two main problems in robotics: the path planning problem and the multi-robot task allocation problem. It is the first book to provide a comprehensive solution for using these techniques in large-scale environments containing randomly scattered obstacles. The research conducted resulted in tangible results both in theory and in practice. For path planning, new algorithms for large-scale problems are devised and implemented and integrated into the Robot Operating System (ROS). The book also discusses the parallelism advantage of cloud computing techniques to solve the path planning problem, and, for multi-robot task allocation, it addresses the task assignment problem and the multiple traveling salesman problem for mobile robots applications. In addition, four new algorithms have been devised to investigate the cooperation issues with extensive simulations and comparative performance evaluation. The algorithms are implemented and simulated in MATLAB and Webots.

Written by Ron Alterovitz and Ken Goldberg, this monograph combines ideas from robotics, physically-based modeling, and operations research to develop new motion planning and optimization algorithms for image-guided medical procedures.

The present book addresses various power system planning issues for professionals as well as senior level and postgraduate students. Its emphasis is on long-term issues, although much of the ideas may be used for short and mid-term cases, with some modifications. Back-up materials are provided in twelve appendices of the book. The readers can use the numerous examples presented within the chapters and problems at the end of the chapters, to make sure that the materials are adequately followed up. Based on what Matlab provides as a powerful package for students and professional, some of the examples and the problems are solved in using M-files especially developed and attached for this purpose. This adds a unique feature to the book for in-depth understanding of the materials, sometimes, difficult to apprehend mathematically. Chapter 1 provides an introduction to Power System Planning (PSP) issues and basic principles. As most of PSP problems are modeled as optimization problems, optimization techniques are covered in some details in Chapter 2. Moreover, PSP decision makings are based on both technical and economic considerations, so economic principles are briefly reviewed in Chapter 3. As a basic requirement of PSP studies, the load has to be known. Therefore, load forecasting is presented in Chapter 4. Single bus Generation Expansion Planning (GEP) problem is described in Chapter 5. This study is performed using WASP-IV, developed by International Atomic Energy Agency. The study ignores the grid structure. A Multi-bus GEP problem is discussed in Chapter 6 in which the transmission effects are, somehow, accounted for. The results of single bus GEP is used as an input to this problem. SEP problem is fully presented in Chapter 7. Chapter 8 devotes to Network Expansion Planning (NEP) problem, in which the network is planned. The results of NEP, somehow, fixes the network structure. Some practical considerations and improvements such as multi-voltage cases are discussed in Chapter 9. As NEP study is typically based on some simplifying assumptions and Direct Current Load Flow (DCLF) analysis, detailed Reactive Power Planning (RPP) study is finally presented in Chapter 10, to guarantee acceptable ACLF performance during normal as well as contingency conditions. This, somehow, concludes the basic PSP problem. The changing environments due to power system restructuring dictate some uncertainties on PSP issues. It is shown in Chapter 11 that how these uncertainties can be accounted for. Although is intended to be a text book, PSP is a research oriented topic, too. That is why Chapter 12 is devoted to research trends in PSP. The chapters conclude with a comprehensive example in Chapter 13, showing the step-by-step solution of a practical case.

Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning, but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the 'configuration spaces' of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. This text and reference is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.