東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Localization strategies for robots i...

Gao, Chao.

Linked to FindBook

Google Book

Amazon

博客來

Localization strategies for robots in outdoor environments with applications to smart wheelchair systems.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Localization strategies for robots in outdoor environments with applications to smart wheelchair systems./
Author:	Gao, Chao.
Description:	158 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-10, Section: B, page: 6407.
Contained By:	Dissertation Abstracts International71-10B.
Subject:	Engineering, Robotics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3419353
ISBN:	9781124192178

Localization strategies for robots in outdoor environments with applications to smart wheelchair systems.
Gao, Chao.

Localization strategies for robots in outdoor environments with applications to smart wheelchair systems. - 158 p.

Source: Dissertation Abstracts International, Volume: 71-10, Section: B, page: 6407.

Thesis (Ph.D.)--Lehigh University, 2010.

During the past decade, research in mobile robotics has transcended the indoor navigation stage. Expanding the application to outdoor navigation, the research community made significant strides recently in terms of vehicle autonomy in DARPA Urban Challenge. However, these successes heavily relied on inertial/GPS navigation systems costing up to

ISBN: 9781124192178Subjects--Topical Terms:

1018454
Engineering, Robotics.

Localization strategies for robots in outdoor environments with applications to smart wheelchair systems.
LDR:03175nam 2200325 4500 001 1405137
005 20111206130415.5
008 130515s2010 ||||||||||||||||| ||eng d
020 $a 9781124192178
035 $a (UMI)AAI3419353
035 $a AAI3419353
040 $a UMI $c UMI
100 1 $a Gao, Chao. $3 1684494
245 1 0 $a Localization strategies for robots in outdoor environments with applications to smart wheelchair systems.
300 $a 158 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-10, Section: B, page: 6407.
500 $a Adviser: John R. Spletzer.
502 $a Thesis (Ph.D.)--Lehigh University, 2010.
520 $a During the past decade, research in mobile robotics has transcended the indoor navigation stage. Expanding the application to outdoor navigation, the research community made significant strides recently in terms of vehicle autonomy in DARPA Urban Challenge. However, these successes heavily relied on inertial/GPS navigation systems costing up to $1 00K or more. Such a solution is impractical in terms of both size and cost for most civilian applications to mobile robots.
520 $a Our vision includes smart wheelchair systems eventually capable of autonomous navigation in unstructured, outdoor environments. As our primary work in this area, the Automated Transport and Retrieval System (ATRS) enables independent mobility for drivers in wheelchairs by automating the stowing and retrieval of the driver's wheelchair system. While ATRS has been commercialized, and its smart wheelchair system does in fact navigate autonomously, its autonomy is limited to an area immediately adjacent to the host vehicle. We would like to build on these results to support a greater range of smart wheelchair applications. Key to this objective is a robust means for outdoor localization.
520 $a This dissertation proposes a map-based localization approach. In this approach, three-dimensional map data are acquired by vehicles employing high precision inertial/GPS systems for pose estimation, in conjunction with high-fidelity light detection and ranging (LIDAR) systems whose range measurements are subsequently registered to a global coordinate frame. The resulting map data are then synthesized a priori to identify robust, salient features for use as landmarks in localization. By leveraging such maps with landmark meta-data, robots possessing far lower cost sensor suites gain many of the benefits obtained from the higher fidelity sensors, but without the cost. Experiments show that by using such a map-based localization approach, a smart wheelchair testing platform outfitted only with a 2-D LIDAR and encoders was able to maintain accurate, global pose estimates outdoors over paths of almost 1km in absence of GPS.
590 $a School code: 0105.
650 4 $a Engineering, Robotics. $3 1018454
690 $a 0771
710 2 $a Lehigh University. $b Computer Engineering. $3 1684495
773 0 $t Dissertation Abstracts International $g 71-10B.
790 1 0 $a Spletzer, John R., $e advisor
790 1 0 $a Lopresti, Daniel P. $e committee member
790 1 0 $a Huang, Xiaolei $e committee member
790 1 0 $a Blum, Rick S. $e committee member
790 $a 0105
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3419353