Task-Directed Sensor Fusion and Planning: A Computational Approach
If you have ever hiked up a steep hill to reach a viewpoint, you will know that sensing can involve the expenditure of effort. More generally, the choice of which movement an intelligent system chooses to make is usually based on information gleaned from sensors. But the information required to make...
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Boston, MA
Springer US
1990
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Schriftenreihe: | The Kluwer International Series in Engineering and Computer Science, Robotics: Vision, Manipulation and Sensors
99 |
Schlagworte: | |
Online-Zugang: | BTU01 URL des Erstveröffentlichers |
Zusammenfassung: | If you have ever hiked up a steep hill to reach a viewpoint, you will know that sensing can involve the expenditure of effort. More generally, the choice of which movement an intelligent system chooses to make is usually based on information gleaned from sensors. But the information required to make the motion decision may not be immediately to hand, so the system . first has to plan a motion whose purpose is to acquire the needed sensor information. Again, this conforms to our everyday experience: I am in the woods and don't know which direction to go, so I climb up to the ridge to get my bearings; I am lost in a new town, so I plan to drive to the next junction where there is sure to be a roadsign, failing that I will ask someone who seems to be from the locality. Why, if experiences such as these are so familiar, has the problem only recently been recognised and studied in Robotics? One reason is that until quite recently Robotics research was dominated by work on robot arms with limited reach and fixed in a workcell |
Beschreibung: | 1 Online-Ressource (XVIII, 254 p) |
ISBN: | 9781461315452 |
DOI: | 10.1007/978-1-4613-1545-2 |
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520 | |a If you have ever hiked up a steep hill to reach a viewpoint, you will know that sensing can involve the expenditure of effort. More generally, the choice of which movement an intelligent system chooses to make is usually based on information gleaned from sensors. But the information required to make the motion decision may not be immediately to hand, so the system . first has to plan a motion whose purpose is to acquire the needed sensor information. Again, this conforms to our everyday experience: I am in the woods and don't know which direction to go, so I climb up to the ridge to get my bearings; I am lost in a new town, so I plan to drive to the next junction where there is sure to be a roadsign, failing that I will ask someone who seems to be from the locality. Why, if experiences such as these are so familiar, has the problem only recently been recognised and studied in Robotics? One reason is that until quite recently Robotics research was dominated by work on robot arms with limited reach and fixed in a workcell | ||
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Datensatz im Suchindex
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any_adam_object | |
author | Hager, Gregory D. |
author_facet | Hager, Gregory D. |
author_role | aut |
author_sort | Hager, Gregory D. |
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dewey-full | 629.8 |
dewey-hundreds | 600 - Technology (Applied sciences) |
dewey-ones | 629 - Other branches of engineering |
dewey-raw | 629.8 |
dewey-search | 629.8 |
dewey-sort | 3629.8 |
dewey-tens | 620 - Engineering and allied operations |
discipline | Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
doi_str_mv | 10.1007/978-1-4613-1545-2 |
format | Electronic eBook |
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id | DE-604.BV045186363 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T08:10:57Z |
institution | BVB |
isbn | 9781461315452 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030575540 |
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physical | 1 Online-Ressource (XVIII, 254 p) |
psigel | ZDB-2-ENG ZDB-2-ENG_Archiv ZDB-2-ENG ZDB-2-ENG_Archiv |
publishDate | 1990 |
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publisher | Springer US |
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series2 | The Kluwer International Series in Engineering and Computer Science, Robotics: Vision, Manipulation and Sensors |
spelling | Hager, Gregory D. Verfasser aut Task-Directed Sensor Fusion and Planning A Computational Approach by Gregory D. Hager Boston, MA Springer US 1990 1 Online-Ressource (XVIII, 254 p) txt rdacontent c rdamedia cr rdacarrier The Kluwer International Series in Engineering and Computer Science, Robotics: Vision, Manipulation and Sensors 99 If you have ever hiked up a steep hill to reach a viewpoint, you will know that sensing can involve the expenditure of effort. More generally, the choice of which movement an intelligent system chooses to make is usually based on information gleaned from sensors. But the information required to make the motion decision may not be immediately to hand, so the system . first has to plan a motion whose purpose is to acquire the needed sensor information. Again, this conforms to our everyday experience: I am in the woods and don't know which direction to go, so I climb up to the ridge to get my bearings; I am lost in a new town, so I plan to drive to the next junction where there is sure to be a roadsign, failing that I will ask someone who seems to be from the locality. Why, if experiences such as these are so familiar, has the problem only recently been recognised and studied in Robotics? One reason is that until quite recently Robotics research was dominated by work on robot arms with limited reach and fixed in a workcell Engineering Control, Robotics, Mechatronics Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence (incl. Robotics) Artificial intelligence Computer graphics Control engineering Robotics Mechatronics Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Sensortechnik (DE-588)4121663-5 gnd rswk-swf Robotik (DE-588)4261462-4 gnd rswk-swf Robotik (DE-588)4261462-4 s Sensortechnik (DE-588)4121663-5 s Künstliche Intelligenz (DE-588)4033447-8 s 1\p DE-604 Erscheint auch als Druck-Ausgabe 9781461288282 https://doi.org/10.1007/978-1-4613-1545-2 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Hager, Gregory D. Task-Directed Sensor Fusion and Planning A Computational Approach Engineering Control, Robotics, Mechatronics Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence (incl. Robotics) Artificial intelligence Computer graphics Control engineering Robotics Mechatronics Künstliche Intelligenz (DE-588)4033447-8 gnd Sensortechnik (DE-588)4121663-5 gnd Robotik (DE-588)4261462-4 gnd |
subject_GND | (DE-588)4033447-8 (DE-588)4121663-5 (DE-588)4261462-4 |
title | Task-Directed Sensor Fusion and Planning A Computational Approach |
title_auth | Task-Directed Sensor Fusion and Planning A Computational Approach |
title_exact_search | Task-Directed Sensor Fusion and Planning A Computational Approach |
title_full | Task-Directed Sensor Fusion and Planning A Computational Approach by Gregory D. Hager |
title_fullStr | Task-Directed Sensor Fusion and Planning A Computational Approach by Gregory D. Hager |
title_full_unstemmed | Task-Directed Sensor Fusion and Planning A Computational Approach by Gregory D. Hager |
title_short | Task-Directed Sensor Fusion and Planning |
title_sort | task directed sensor fusion and planning a computational approach |
title_sub | A Computational Approach |
topic | Engineering Control, Robotics, Mechatronics Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence (incl. Robotics) Artificial intelligence Computer graphics Control engineering Robotics Mechatronics Künstliche Intelligenz (DE-588)4033447-8 gnd Sensortechnik (DE-588)4121663-5 gnd Robotik (DE-588)4261462-4 gnd |
topic_facet | Engineering Control, Robotics, Mechatronics Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence (incl. Robotics) Artificial intelligence Computer graphics Control engineering Robotics Mechatronics Künstliche Intelligenz Sensortechnik Robotik |
url | https://doi.org/10.1007/978-1-4613-1545-2 |
work_keys_str_mv | AT hagergregoryd taskdirectedsensorfusionandplanningacomputationalapproach |