Just went through this book in a week for my own research. This was a nice read and a great reference book for all the probabilistic theory and algorithms that are essential to robotics and AI these days, in cutting edge research. Strongly recommended as a book that you will want to keep on your closest shelf or desk corner. Be warned that this is definitely a graduate-level textbook, so don't see this as a "robotics for dummies" kind of book, be prepared with at least some prior basis in probabilistic methods, estimation, and/or machine learning. This book will be a great jump forward into robotics for a finishing undergraduate, or a firm reference book for graduate students or researchers. The amount of mathematical derivations is just about perfect (doesn't break readability, but provides just enough to avoid any "mathemagical" leaps in the formulations). Algorithms are concise, concrete and pertinent (as opposed to many other probabilistic texts that present algorithms that are often written in very high-level pseudo-code that makes it hard to understand what a concrete implementation really involves doing). Lots of concrete examples that make it really clear why this paradigm for robotics software is necessary and by far the most powerful (although a real computational challenge!).