Mobile Robotics: Mathematics Models and Methods

This book was originally written to record the content for my graduate course in mobile robots - taught at the Robotics Institute since the 1990s. It is intended to be useful for both teaching and for engineers who want a solid grounding in the fundamental topics of the field. Some of the mathematics may be beyond undergraduate level, depending on your background, but motivated readers with an undergraduate exposure to STEM disciplines should be able to master the contents.

The book makes no attempt to survey all of the relevant literature or to inform researchers on latest developments and I could not possibly reference every paper that is relevant or even significant for each topic. The book is intended to capture at least some of what is durably fundamental about the theory and practice of mobile robotics.

The Publisher website for the book is www.cambridge.org/9781107031159 . There you will be able to preview its contents.

You can buy the book online (paper or ebook) at Amazon here: http://www.amazon.com/Mobile-Robotics-Mathematics-Models-Methods/dp/110703115X

Errata

Click here to access a pdf file containing a list of errata in the original revision. If you find any more, please send me an email with a message whose subject line starts with [MR_BOOK ERRATA].

Lecture Slides

I have taught a graduate course from this material for many years but I must admit that over time I have generated more material than can fit in a single 13 week course. Nonetheless, there are slides available below for the entire book. I would like to hear your feedback. Send me a message with subject sarting with [MR_BOOK SLIDES].

The slides follow the book very closely with numbering that allows the user to find the appropriate part of the book very quickly. Missing page numbers are caused by hidden slides, which mostly contain earlier revisions. PDFs are provided to reduce memory footprint. Videos are large. For that reason, and also because at least some are not mine to be distributing so broadly, and I no longer know which is which, they are not included.

Introduction
Math 1: Conventions, Matrices Transforms	Math 2: Kinematics: Mechanisms, Orientation, Angular Velocity	Math 3: Kinematics: Cameras and Rangefinders	Math 4: Transform Graphs and Pose Networks	Math 5: Quaternions
Num 1: Linearization and Optimization	Num 2: Systems of Equations, Nonlinear and Constrained Optimization	Num 3: Differential Algebraic Systems, ODE Integration
Dyn 1: Moving Coordinates, WMR Kinematics	Dyn 2: Constrained Kinematics and Dynamics	Dyn 3: Linear Dynamical Systems, System Identification
Unc 1: Random Variables, Processes, and Transformation	Unc 2: Covariance Propagation, Optimal Estimation	Unc 3: State Space Kalman Filters	Unc 4: Bayesian Estimation
StateEst 1: Mathematics of State Estimation	StateEst 2: Sensors for State Estimation	StateEst 3: Inertial Navigation Systems	StateEst 4: Satellite Navigation Systems
Ctrl 1: Classical Control	Ctrl 2: State Space Control	Ctrl 3: Optimal and Model Predictive Control	Ctrl 4: Intelligent Control
Perc 1: Image Processing Operators and Algorithms	Perc 2: Physics and Principles of Radiative Sensors	Perc 3: Sensors for Perception	Perc 4: Aspects of Geometric and Semantic Computer Vision
Map 1: Representation and Issues	Map 2: Visual Localization and Motion Estimation	Map 3: Simultaneous Localization and Mapping
Plan 1: Introduction	Plan 2: Representation and Search for Global Motion Planning	Plan 3: Real Time Global Motion Planningy

Solutions

Solutions to chapter exercises are available here under the resources link, but only after you can demonstrate to the publisher's satisfaction that you are not a student.

Last-Modified: June 2015