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Probabilistic Robotics (Intelligent Robotics & Autonomous Agents Series) Hardcover – 20 Sep 2005

3.0 out of 5 stars 1 customer review

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Product details

  • Hardcover: 668 pages
  • Publisher: MIT Press (20 Sept. 2005)
  • Language: English
  • ISBN-10: 0262201623
  • ISBN-13: 978-0262201629
  • Product Dimensions: 20.3 x 2.9 x 22.9 cm
  • Average Customer Review: 3.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Bestsellers Rank: 190,991 in Books (See Top 100 in Books)

Product Description

Review

"*Probabilistic Robotics* is a tour de force, replete with material for students and practitioners alike."--Gaurav S. Sukhatme, Associate Professor of Computer Science and Electrical Engineering, University of Southern CaliforniaPlease note: Arrived too late to appear on book jacket.

About the Author

Dieter Fox is Associate Professor of Computer Science at the University of Washington.


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Top Customer Reviews

Format: Kindle Edition Verified Purchase
The book is strongly suggested by the lecturer for the robotics. However, what a disappointed is that the book now is not compatible with Eink kindle, like to say the Voyage. Kindle lovers you should be careful.
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: 4.6 out of 5 stars 35 reviews
5.0 out of 5 stars Brilliant 13 May 2014
By Sergey Popov - Published on Amazon.com
Format: Hardcover Verified Purchase
This is a brilliant book, must read and must have on a desk of a robotics engineer, especially on the software side.
One can tell how much effort and hard work the authors put into writing the book.
Very clean and concise text.
The book not just teaches the subject, but gives a lot of ideas on further research topics.
It might sound like the authors have been primarily concerned with SLAM and motion planning problems. The truth is that the methods they describe can be applied in many other areas, just use your brain.
Wish there were more books like that.
2 of 2 people found the following review helpful
4.0 out of 5 stars The Robotics Reference 25 July 2010
By Chris Mansley - Published on Amazon.com
Format: Hardcover Verified Purchase
This textbook is the standard reference for probabilistic robotics in the areas of navigation and mapping. One of the authors is the director of the Stanford AI lab and headed the winning entry in the DARPA Grand Challenge in 2007, which needless to say means he understands and has developed many of the techniques in the book. The algorithms are laid out and explained at different depths of understanding, which sometimes allows them to be used without reading the rigorous mathematical derivations that are included. Within the first week of having this book, I found that my method of estimating odometry in the prediction step of a Kalman filter could be improved with a different estimation. In addition, since the book provided a mathematical derivation, I could compare the two techniques and explain under what assumptions my approximation fails to do well.
1 of 1 people found the following review helpful
5.0 out of 5 stars Very comprehensive 1 May 2014
By peter - Published on Amazon.com
Format: Hardcover Verified Purchase
Short of writing your code for you, this tolme, provides general algorithms that can be applied to any sensor or configuration. It is not comprehensive in the number of variations on the basic algorithm, but allows sufficient background understanding to allow users to research specific variations from other publications with a modest chance of understanding the theory behind it.
1 of 1 people found the following review helpful
5.0 out of 5 stars Great book from a great roboticist. 6 May 2014
By Orlando Garcia Alvarez - Published on Amazon.com
Format: Hardcover Verified Purchase
Excellent book for master degree students in robotics, it contains a large variety of topics which are just explored enough to understand and to allow you for further research. The conditions of the book were great, just a small scratch on a corner probably due to the delivery process. The book is totally recommended. Greetings.
2 of 3 people found the following review helpful
5.0 out of 5 stars A great treatment of the subject 17 Jun. 2014
By Thomas Edward - Published on Amazon.com
Format: Hardcover Verified Purchase
I work in avionics, not robotics, but I ordered this book because it seemed to cover a lot of the subjects that are now making their way into avionics systems. In particular, I was interested in its coverage of Kalman Filters and POMDPs.

I have to say that the other positive reviews are well-warranted. I have not before encountered such clear explanations of Bayes filtering, Kalman Filters (including EKFs and UKFs), even in spite of having encountered many books and papers on these subjects. The authors seem to go out of their way to present the material with a logical and clear-cut progression that doesn't skip essential steps with the typical "the reader can clearly see that..." kinds of hand-waiving I have seen in other texts.

To be honest, I can't comment on the parts related to robot dynamics and SLAM, but as for chapters 1-4 and the chapters on POMDPs, I would have to say that this book presents the material in a better and more clear way than I have ever seen it presented before.
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