---
product_id: 2793383
title: "Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)"
price: "B/.315"
currency: PAB
in_stock: true
reviews_count: 13
url: https://www.desertcart.com.pa/products/2793383-probabilistic-robotics-intelligent-robotics-and-autonomous-agents-series
store_origin: PA
region: Panama
---

# Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)

**Price:** B/.315
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- **What is this?** Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)
- **How much does it cost?** B/.315 with free shipping
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## Description

Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series) [Thrun, Sebastian, Burgard, Wolfram, Fox, Dieter] on desertcart.com. *FREE* shipping on qualifying offers. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)

Review: Great Reference Book! - 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!).
Review: A great treatment of the subject - 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.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #106,608 in Books ( See Top 100 in Books ) #18 in Robotics (Books) #38 in Robotics & Automation (Books) #70 in Probability & Statistics (Books) |
| Customer Reviews | 4.7 4.7 out of 5 stars (181) |
| Dimensions  | 8.19 x 1.25 x 9.31 inches |
| Edition  | Intelligent Robotics and Autonomous Agents series |
| ISBN-10  | 0262201623 |
| ISBN-13  | 978-0262201629 |
| Item Weight  | 2.93 pounds |
| Language  | English |
| Print length  | 672 pages |
| Publication date  | August 19, 2005 |
| Publisher  | The MIT Press |

## Images

![Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series) - Image 1](https://m.media-amazon.com/images/I/71-F1+2p7lL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Great Reference Book!
*by M***E on December 26, 2010*

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!).

### ⭐⭐⭐⭐⭐ A great treatment of the subject
*by T***D on June 17, 2014*

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.

### ⭐⭐⭐⭐⭐ Best explanation of the Kalman filter I have read yet.
*by M***6 on June 10, 2013*

As someone with a multi-discipline background that includes some control theory, I am always frustrated by the "explanations" that control theorists attempt to put forward for the Kalman filter, and find that the best explanations actually come from other fields. Prior to stumbling upon this book, the best explanation of the Kalman filter I had read actually came from a book on Bayesian statistics. It makes sense that this book would have the same basic Bayesian approach, but would also extend the technique in exactly the manner needed to properly do controls and robotics. Further it fits the technique into a larger, cross-disciplinary, landscape of estimation, sensing and modeling techniques from both "controls" and "robotics" (which, despite sounding like two forms of the same field, tend to actually have distinct and disparate communities which have surprising trouble talking to one another).

## Frequently Bought Together

- Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series)
- Planning Algorithms
- Modern Robotics: Mechanics, Planning, and Control

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*Last updated: 2026-02-26*