東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Compact Representations for Efficien...

Dobson, Andrew.

FindBook

Google Book

Amazon

博客來

Compact Representations for Efficient Robot Motion Planning with Formal Guarantees.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Compact Representations for Efficient Robot Motion Planning with Formal Guarantees./
作者:	Dobson, Andrew.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	172 p.
附註:	Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
Contained By:	Dissertation Abstracts International79-08B(E).
標題:	Computer science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10799896
ISBN:	9780355780901

Compact Representations for Efficient Robot Motion Planning with Formal Guarantees.
Dobson, Andrew.

Compact Representations for Efficient Robot Motion Planning with Formal Guarantees. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 172 p.

Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.

Thesis (Ph.D.)--Rutgers The State University of New Jersey - New Brunswick, 2017.

This work provides compact representations for single- and multi-robot motion planning in the context of prehensile robot manipulation. This work describes the asymptotic near-optimality and probabilistic near-optimality properties of these planners. Probabilistic near-optimality is leveraged to provide practical and grounded stopping criteria for these methods which probabilistically guarantee the methods return high-quality paths. It is also shown how these methods can be leveraged to produce a compact planning representation, which is a lightweight structure that is quick to query and easy to store. The work also outlines a compact representation for solving multi-arm manipulation tasks, and integrates a scalable, asymptotically optimal multi-robot motion planning method to provide scalable, globally asymptotically optimal task and motion planning in manipulation domains.

ISBN: 9780355780901Subjects--Topical Terms:

523869
Computer science.

Compact Representations for Efficient Robot Motion Planning with Formal Guarantees.
LDR:01859nmm a2200289 4500 001 2159871
005 20180703084809.5
008 190424s2017 ||||||||||||||||| ||eng d
020 $a 9780355780901
035 $a (MiAaPQ)AAI10799896
035 $a (MiAaPQ)rutgersnb:8356
035 $a AAI10799896
040 $a MiAaPQ $c MiAaPQ
100 1 $a Dobson, Andrew. $3 562280
245 1 0 $a Compact Representations for Efficient Robot Motion Planning with Formal Guarantees.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 172 p.
500 $a Source: Dissertation Abstracts International, Volume: 79-08(E), Section: B.
500 $a Adviser: Kostas E. Bekris.
502 $a Thesis (Ph.D.)--Rutgers The State University of New Jersey - New Brunswick, 2017.
520 $a This work provides compact representations for single- and multi-robot motion planning in the context of prehensile robot manipulation. This work describes the asymptotic near-optimality and probabilistic near-optimality properties of these planners. Probabilistic near-optimality is leveraged to provide practical and grounded stopping criteria for these methods which probabilistically guarantee the methods return high-quality paths. It is also shown how these methods can be leveraged to produce a compact planning representation, which is a lightweight structure that is quick to query and easy to store. The work also outlines a compact representation for solving multi-arm manipulation tasks, and integrates a scalable, asymptotically optimal multi-robot motion planning method to provide scalable, globally asymptotically optimal task and motion planning in manipulation domains.
590 $a School code: 0190.
650 4 $a Computer science. $3 523869
690 $a 0984
710 2 $a Rutgers The State University of New Jersey - New Brunswick. $b School of Graduate Studies. $3 3347771
773 0 $t Dissertation Abstracts International $g 79-08B(E).
790 $a 0190
791 $a Ph.D.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10799896