Robotics: Modelling, Planning and Control (Advanced Textbooks in Control and Signal Processing) Review

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(More customer reviews)This book has everything a new grad student or aspiring roboticist would want. It covers the mechanics, the controls and even some vision for robotic manipulators. Very nice resource.

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Based on the successful Modelling and Control of Robot Manipulators by Sciavicco and Siciliano (Springer, 2000), Robotics provides the basic know-how on the foundations of robotics: modelling, planning and control. It has been expanded to include coverage of mobile robots, visual control and motion planning. A variety of problems is raised throughout, and the proper tools to find engineering-oriented solutions are introduced and explained.The text includes coverage of fundamental topics like kinematics, and trajectory planning and related technological aspects including actuators and sensors.To impart practical skill, examples and case studies are carefully worked out and interwoven through the text, with frequent resort to simulation. In addition, end-of-chapter exercises are proposed, and the book is accompanied by an electronic solutions manual containing the MATLAB code for computer problems; this is available free of charge to those adopting this volume as a textbook for courses.

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Advanced Kalman Filtering, Least-Squares and Modeling: A Practical Handbook Review

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(More customer reviews)The most thorough and complete work I have seen on the subject. This provides a lot of in-depth information and insight into various areas not found elsewhere. While quite a bit of theory is presented, the main concentration is providing practical information useful for a wide variety of filter implementations. This will be most useful for somebody with a strong mathematical background, particularly in linear algebra, who is looking for a comprehensive understanding and the best solution for a particular application.

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This book provides a complete explanation of estimation theory andapplication, modeling approaches, and model evaluation. Each topicstarts with a clear explanation of the theory (often includinghistorical context), followed by application issues that should beconsidered in the design. Different implementations designed to addressspecific problems are presented, and numerous examples of varyingcomplexity are used to demonstrate the concepts.This book is intended primarily as a handbook for engineers who must design practical systems. Its primarygoal is to explain all important aspects of Kalman filtering and least-squares theory and application. Discussion of estimator design and model development is emphasized so that the reader may develop an estimator that meets all application requirements and is robust to modeling assumptions. Since it is sometimes difficult to a priori determine the best model structure, use of exploratory data analysis to define model structure is discussed. Methods for deciding on the "best" model are also presented. A second goal is to present little known extensions of least squares estimation or Kalman filtering that provide guidance on model structure and parameters, or make the estimator more robust to changes in real-world behavior.A third goal is discussion of implementation issues that make the estimator more accurate or efficient, or that make it flexible so that model alternatives can be easily compared.The fourth goal is to provide the designer/analyst with guidance in evaluating estimator performance and in determining/correcting problems.The final goal is to provide a subroutine library that simplifies implementation, and flexible general purpose high-level drivers that allow both easy analysis of alternative models and access to extensions of the basic filtering.

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