State estimation for robotics:
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:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge
Cambridge University Press
2017
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| Subjects: | |
| Online Access: | BSB01 FHN01 UER01 Volltext |
| Summary: | 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 |
| Item Description: | Title from publisher's bibliographic system (viewed on 28 Aug 2017) |
| Physical Description: | 1 online resource (xii, 368 pages) |
| ISBN: | 9781316671528 |
| DOI: | 10.1017/9781316671528 |
Staff View
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Record in the Search Index
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| dewey-full | 629.8/9201512482 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
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| dewey-search | 629.8/9201512482 |
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| dewey-tens | 620 - Engineering and allied operations |
| discipline | Informatik Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
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| id | DE-604.BV044727912 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:00:31Z |
| institution | BVB |
| isbn | 9781316671528 |
| language | English |
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| publishDate | 2017 |
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| publisher | Cambridge University Press |
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| spelling | Barfoot, Tim 1973- Verfasser (DE-588)105431215X aut State estimation for robotics Timothy D. Barfoot Cambridge Cambridge University Press 2017 1 online resource (xii, 368 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 28 Aug 2017) 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 Robots Control systems Observers (Control theory) Mathematics Lie groups Robotik (DE-588)4261462-4 gnd rswk-swf Lagemessung (DE-588)4206329-2 gnd rswk-swf Positionierung (DE-588)4140478-6 gnd rswk-swf Lagemessung (DE-588)4206329-2 s Positionierung (DE-588)4140478-6 s Robotik (DE-588)4261462-4 s 1\p DE-604 Erscheint auch als Druck-Ausgabe 9781107159396 https://doi.org/10.1017/9781316671528 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Barfoot, Tim 1973- State estimation for robotics Robots Control systems Observers (Control theory) Mathematics Lie groups Robotik (DE-588)4261462-4 gnd Lagemessung (DE-588)4206329-2 gnd Positionierung (DE-588)4140478-6 gnd |
| subject_GND | (DE-588)4261462-4 (DE-588)4206329-2 (DE-588)4140478-6 |
| title | State estimation for robotics |
| title_auth | State estimation for robotics |
| title_exact_search | State estimation for robotics |
| title_full | State estimation for robotics Timothy D. Barfoot |
| title_fullStr | State estimation for robotics Timothy D. Barfoot |
| title_full_unstemmed | State estimation for robotics Timothy D. Barfoot |
| title_short | State estimation for robotics |
| title_sort | state estimation for robotics |
| topic | Robots Control systems Observers (Control theory) Mathematics Lie groups Robotik (DE-588)4261462-4 gnd Lagemessung (DE-588)4206329-2 gnd Positionierung (DE-588)4140478-6 gnd |
| topic_facet | Robots Control systems Observers (Control theory) Mathematics Lie groups Robotik Lagemessung Positionierung |
| url | https://doi.org/10.1017/9781316671528 |
| work_keys_str_mv | AT barfoottim stateestimationforrobotics |