Overview
Safe Robot Navigation Among Moving and Steady Obstacles is the first book to focus on reactive navigation algorithms in unknown dynamic environments with moving and steady obstacles. The first three chapters provide introduction and background on sliding mode control theory, sensor models, and vehicle kinematics. Chapter 4 deals with the problem of optimal navigation in the presence of obstacles. Chapter 5 discusses the problem of reactively navigating. In Chapter 6, border patrolling algorithms are applied to a more general problem of reactively navigating. A method for guidance of a Dubins-like mobile robot is presented in Chapter 7. Chapter 8 introduces and studies a simple biologically-inspired strategy for navigation a Dubins-car. Chapter 9 deals with a hard scenario where the environment of operation is cluttered with obstacles that may undergo arbitrary motions, including rotations and deformations. Chapter 10 presents a novel reactive algorithm for collision free navigation of a nonholonomic robot in unknown complex dynamic environments with moving obstacles. Chapter 11 introduces and examines a novel purely reactive algorithm to navigate a planar mobile robot in densely cluttered environments with unpredictably moving and deforming obstacles. Chapter 12 considers a multiple robot scenario. For the Control and Automation Engineer, this book offers accessible and precise development of important mathematical models and results. All the presented results have mathematically rigorous proofs. On the other hand, the Engineer in Industry can benefit by the experiments with real robots such as Pioneer robots, autonomous wheelchairs and autonomous mobile hospital.
Full Product Details
Author: Andrey V. Savkin (Professor, School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia) ,
Alexey S. Matveev (Full Professor, Department of Mathematics and Mechanics, Saint Petersburg University, Russia) ,
Michael Hoy (Quantitative Analyst, Financial services industry) ,
Chao Wang (Postdoctoral Researcher, University of New South Wales)
Publisher: Elsevier - Health Sciences Division
Imprint: Butterworth-Heinemann Inc
Dimensions:
Width: 15.20cm
, Height: 1.80cm
, Length: 22.90cm
Weight: 0.570kg
ISBN: 9780128037300
ISBN 10: 012803730
Pages: 358
Publication Date: 03 September 2015
Audience:
Professional and scholarly
,
Professional & Vocational
Format: Paperback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Author Information
Prof. Andrey V. Savkin received M.S. and Ph.D. degrees in mathematics from the Leningrad State University, Saint Petersburg, Russia, in 1987 and 1991, respectively. From 1987 to 1992, he was with the Television Research Institute, Leningrad, Russia. From 1992 to 1994, he held a Postdoctoral position in the Department of Electrical Engineering, Australian Defence Force Academy, Canberra. From 1994 to 1996, he was a Research Fellow in the Department of Electrical and Electronic Engineering and the Cooperative Research Centre for Sensor Signal and Information Processing, University of Melbourne, Australia. From 1996 to 2000, he was a Senior Lecturer, and then an Associate Professor in the Department of Electrical and Electronic Engineering, University of Western Australia, Perth. Since 2000, he has been a Professor in the School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, NSW, Australia. His current research interests include robust control and state estimation, hybrid dynamical systems, guidance, navigation and control of mobile robots, applications of control and signal processing in biomedical engineering and medicine. He has authored and co-authored 5 research monograph (published by Birkhauser and IEEE Press/Wiley) and about 100 journal papers. Almost all Matveev's journal publications are in top international journals, such as “Automatica, “International Journal of Control, “IEEE Transactions on Automatic Control. Prof. Matveev is responsible for many theoretical advances in the areas of optimal control, hybrid systems, networked control systems, and robot navigation.
