Mobile Robot Localization and Map Building: A Multisensor Fusion Approach
by Jose A. Castellanos and Juan D. Tardós
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The main problems described throughout this book are:
- Representation and integration of uncertain geometric information by means of the Symmetries and Perturbations Model (SPmodel). This model combines the use of probability theory to represent the imprecision in the location of a geometric element, and the theory of symmetries to represent the partiality due to characteristics of each type of geometric element.
- A solution to the first location problem, that is, the computation of an estimation for the mobile robot location when the vehicle is completely lost in the environment. The problem is formulated as a search in an interpretation tree using efficient matching algorithms and geometric constraints to reduce the size of the solution space.
- The book proposes a new probabilistic framework adapted to the problem of simultaneous localization and map building for mobile robots: the Symmetries and Perturbations Map (SPmap). This framework has been experimentally validated by a complete experiment which profited from ground-truth to accurately validate the precision and the appropriateness of the approach.
The book, Mobile Robot Localization and Map Building: A Multisensor Fusion Approach [Bulk, Wholesale, Quantity] ISBN#9780792377894 in Hardcover by Jose A. Castellanos, Juan D. Tardós may be ordered in bulk quantities. Minimum starts at 25 copies. Availability based on publisher status and quantity being ordered.
Details
- Publisher
- Springer US
- Authors
- Jose A. Castellanos, Juan D. Tardós
- Format
- Hardcover
- Published
- Mar 31, 2000
- ISBN-13
- 9780792377894
- Pages
- 205
Mobile Robot Localization and Map Building for groups: pricing
Volume pricing applies automatically in your cart. No codes, no account needed.
| Copies | Price per copy | You save |
|---|---|---|
| 25 – 49 | $149.59 | 12% off list |
| 50 – 99 | $147.89 | 13% off list |
| 100+ | $146.19 | 14% off list |
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Mobile Robot Localization and Map Building: A Multisensor Fusion Approach
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