State estimation for robotics / Timothy D. Barfoot, University of Toronto.
A key aspect of robotics today is estimating the state, such as position and orientation, of a robot as it moves through the world. Most robots and autonomous vehicles depend on noisy data from sensors such as cameras or laser rangefinders to navigate in a three-dimensional world. This book presents...
Saved in:
| Online Access: |
Full Text (via Cambridge) |
|---|---|
| Main Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge, United Kingdom ; New York, NY, USA :
Cambridge University Press,
2017
|
| Subjects: |
MARC
| LEADER | 00000cam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | in00000057986 | ||
| 006 | m o d | ||
| 007 | cr ||||||||||| | ||
| 008 | 170814s2017 enk ob 001 0 eng d | ||
| 005 | 20230831181036.4 | ||
| 035 | |a (OCoLC)ceba1000443704 | ||
| 037 | |a ceba9781316671528 | ||
| 040 | |a YDX |b eng |e pn |c YDX |d OCLCO |d LGG |d UIU |d HEBIS |d UPM |d OCLCQ |d OCLCF |d AFU |d AU@ |d U3W |d OTZ |d LVT |d MERER |d OCLCQ |d K6U |d OCLCO |d UKAHL |d OCLCQ |d OCLCO |d OCLCQ | ||
| 019 | |a 1042807670 | ||
| 020 | |a 9781316671528 |q (electronic bk.) | ||
| 020 | |a 1316671526 |q (electronic bk.) | ||
| 020 | |z 9781107159396 | ||
| 020 | |z 1107159393 | ||
| 024 | 8 | |a 99973357599 | |
| 029 | 1 | |a AU@ |b 000060932631 | |
| 035 | |a (OCoLC)1000443704 |z (OCoLC)1042807670 | ||
| 050 | 4 | |a TJ211.35 |b .B37 2017 | |
| 049 | |a GWRE | ||
| 100 | 1 | |a Barfoot, Timothy D., |d 1973- |e author. | |
| 245 | 1 | 0 | |a State estimation for robotics / |c Timothy D. Barfoot, University of Toronto. |
| 264 | 1 | |a Cambridge, United Kingdom ; |a New York, NY, USA : |b Cambridge University Press, |c 2017 | |
| 300 | |a 1 online resource (xii, 368 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a pt. 1. Estimation Machinery -- pt. 2. Three-Dimensional Machinery -- pt. 3. Applications | |
| 520 | |a A key aspect of robotics today is estimating the state, such as position and orientation, of a robot as it moves through the world. Most robots and autonomous vehicles depend on noisy data from sensors such as cameras or laser rangefinders to navigate in a three-dimensional world. This book presents common sensor models and practical advice on how to carry out state estimation for rotations and other state variables. It covers both classical state estimation methods such as the Kalman filter, as well as important modern topics such as batch estimation, the Bayes filter, sigmapoint and particle filters, robust estimation for outlier rejection, and continuous-time trajectory estimation and its connection to Gaussian-process regression. The methods are demonstrated in the context of important applications such as point-cloud alignment, pose-graph relaxation, bundle adjustment, and simultaneous localization and mapping. Students and practitioners of robotics alike will find this a valuable resource. | ||
| 650 | 0 | |a Robots |x Control systems. | |
| 650 | 0 | |a Observers (Control theory) |x Mathematics. | |
| 650 | 0 | |a Lie groups. | |
| 650 | 7 | |a Lie groups. |2 fast |0 (OCoLC)fst00998135 | |
| 650 | 7 | |a Robots |x Control systems. |2 fast |0 (OCoLC)fst01099044 | |
| 776 | 0 | 8 | |i Print version: |a Barfoot, Timothy D., 1973- |t State estimation for robotics. |d Cambridge, United Kingdom ; New York, NY, USA : Cambridge University Press, 2017 |z 9781107159396 |z 1107159393 |w (DLC) 2017010237 |w (OCoLC)979533933 |
| 856 | 4 | 0 | |u https://colorado.idm.oclc.org/login?url=https://doi.org/10.1017/9781316671528 |z Full Text (via Cambridge) |
| 915 | |a - | ||
| 956 | |a Cambridge EBA | ||
| 956 | |b Cambridge EBA ebooks Complete Collection | ||
| 998 | |b New collection CUP.ebaebookscomplete | ||
| 994 | |a 92 |b COD | ||
| 999 | f | f | |s aacda085-3a59-4529-9528-1941c2689454 |i ada1a0cf-0918-420f-817f-0978b3953a47 |
| 952 | f | f | |p Can circulate |a University of Colorado Boulder |b Online |c Online |d Online |h Library of Congress classification |i web |