1.

Record Nr.

UNINA9910464543603321

Autore

Wang Zhan

Titolo

Simultaneous localization and mapping [[electronic resource] ] : exactly sparse information filters / / Zhan Wang, Shoudong Huang, Gamini Dissanayake

Pubbl/distr/stampa

Singapore ; ; Hackensack, N.J., : World Scientific, c2011

ISBN

1-283-43379-6

9786613433794

981-4350-32-X

Descrizione fisica

1 online resource (208 p.)

Collana

New frontiers in robotics ; ; v. 3

Altri autori (Persone)

HuangShoudong <1969->

DissanayakeGamini

Disciplina

629.892637

Soggetti

Mobile robots

Robots - Control systems

Sparse matrices

Robotics

Mappings (Mathematics)

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p. 180-194).

Nota di contenuto

Contents; Preface; Acknowledgments; Chapter 1 Introduction; 1.1 The SLAM Problem and Its Applications; 1.1.1 Description of the SLAM Problem; 1.1.2 Applications of SLAM; 1.2 Summary of SLAM Approaches; 1.2.1 EKF/EIF based SLAM Approaches; 1.2.2 Other SLAM Approaches; 1.3 Key Properties of SLAM; 1.3.1 Observability; 1.3.2 EKF SLAM Convergence; 1.3.3 EKF SLAM Consistency; 1.4 Motivation; 1.5 Book Overview; Chapter 2 Sparse Information Filters in SLAM; 2.1 Information Matrix in the Full SLAM Formulation; 2.2 Information Matrix in the Conventional EIF SLAM Formulation

2.3 Meaning of Zero Off-diagonal Elements in Information Matrix2.4 Conditions for Achieving Exact Sparseness; 2.5 Strategies for Achieving Exact Sparseness; 2.5.1 Decoupling Localization and Mapping; 2.5.2 Using Local Submaps; 2.5.3 Combining Decoupling and Submaps; 2.6 Important Practical Issues in EIF SLAM; 2.7 Summary; Chapter 3



Decoupling Localization and Mapping; 3.1 The D-SLAM Algorithm; 3.1.1 Extracting Map Information from Observations; 3.1.2 Key Idea of D-SLAM; 3.1.3 Mapping; 3.1.4 Localization; 3.2 Structure of the Information Matrix in D-SLAM

3.3 Efficient State and Covariance Recovery3.3.1 Recovery Using the Preconditioned Conjugated Gradient (PCG) Method; 3.3.2 Recovery Using Complete Cholesky Factorization; 3.4 Implementation Issues; 3.4.1 Admissible Measurements; 3.4.2 Data Association; 3.5 Computer Simulations; 3.6 Experimental Evaluation; 3.6.1 Experiment in a Small Environment; 3.6.2 Experiment Using the Victoria Park Dataset; 3.7 Computational Complexity; 3.7.1 Storage; 3.7.2 Localization; 3.7.3 Mapping; 3.7.4 State and Covariance Recovery; 3.8 Consistency of D-SLAM; 3.9 Bibliographical Remarks; 3.10 Summary

Chapter 4 D-SLAM Local Map Joining Filter4.1 Structure of D-SLAM Local Map Joining Filter; 4.1.1 State Vectors; 4.1.2 Relative Information Relating Feature Locations; 4.1.3 Combining Local Maps Using Relative Information; 4.2 Obtaining Relative Location Information in Local Maps; 4.2.1 Generating a Local Map; 4.2.2 Obtaining Relative Location Information in the Local Map; 4.3 Global Map Update; 4.3.1 Measurement Model; 4.3.2 Updating the Global Map; 4.3.3 Sparse Information Matrix; 4.4 Implementation Issues; 4.4.1 Robot Localization; 4.4.2 Data Association; 4.4.3 State and Covariance Recovery

4.4.4 When to Start a New Local Map4.5 Computational Complexity; 4.5.1 Storage; 4.5.2 Local Map Construction; 4.5.3 Global Map Update; 4.5.4 Rescheduling the Computational Effort; 4.6 Computer Simulations; 4.6.1 Simulation in a Small Area; 4.6.2 Simulation in a Large Area; 4.7 Experimental Evaluation; 4.8 Bibliographical Remarks; 4.9 Summary; Chapter 5 Sparse Local Submap Joining Filter; 5.1 Structure of Sparse Local Submap Joining Filter; 5.1.1 Input to SLSJF - Local Maps; 5.1.2 Output of SLSJF - One Global Map; 5.2 Fusing Local Maps into the Global Map

5.2.1 Adding XG(k+1)s into the Global Map

Sommario/riassunto

Simultaneous localization and mapping (SLAM) is a process where an autonomous vehicle builds a map of an unknown environment while concurrently generating an estimate for its location. This book is concerned with computationally efficient solutions to the large scale SLAM problems using exactly sparse Extended Information Filters (EIF). The invaluable book also provides a comprehensive theoretical analysis of the properties of the information matrix in EIF-based algorithms for SLAM. Three exactly sparse information filters for SLAM are described in detail, together with two efficient and exact methods for recovering the state vector and the covariance matrix. Proposed algorithms are extensively evaluated both in simulation and through experiments.



2.

Record Nr.

UNINA9910258748903321

Autore

Chuang Hui-Ping

Titolo

Das Steininschriftenprojekt des Wolkenheimklosters während der Liao-Dynastie (907-1125) : Eine Analyse seiner Kolophone / / Hui-Ping Chuang

Pubbl/distr/stampa

De Gruyter, 2018

Berlin ; ; Boston : , : De Gruyter, , [2017]

©2018

ISBN

9783110533736

3110533731

Edizione

[1st ed.]

Descrizione fisica

1 online resource (340 p.)

Collana

Materiale Textkulturen ; ; 17

Disciplina

930

Soggetti

Kolophone

Liao Dynasty

Liao-Dynastie

Steininschriften

colophones

inscriptions

Kanon

Inschrift

Buddhismus

HISTORY / Ancient / General

Academic theses.

History

China History Liao dynasty, 947-1125

China

Lingua di pubblicazione

Tedesco

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Frontmatter -- Inhalt -- Abkürzungsverzeichnis -- Abbildungsverzeichnis -- Tabellenverzeichnis -- Zum Geleit / Ledderose, Lothar -- Danksagung / Hui-Ping, Chuang -- 1. Einführung -- 2. Erste Phase: Wiederbeginn (1027-1056) -- 3. Zweite Phase:



Routine (1058-1093) -- 4. Dritte Phase: Höhepunkt (1093-1095) -- 5. Vierte Phase: Erbe (1107-1121) -- 6. Schlusswort -- Bibliographie -- Register

Sommario/riassunto

Zwischen 616 und 1180 meißelten buddhistische Mönche des rund 75 km südwestlich von Beijing gelegenen Wolkenheimklosters buddhistische Sutren in Stein, um die heiligen Schriften vor dem erwarteten Weltende zu retten. Am Ende dieses wahrscheinlich größten epigraphischen Projektes der Weltgeschichte waren rund 1.600 Texte auf 15.000 Platten mit insgesamt etwa 31 Millionen Schriftzeichen fertiggestellt. Die für das Steininschriftenprojekt wohl bedeutendste Phase war die Zeit der Liao-Dynastie (907-1125), als in nicht einmal 100 Jahren beinahe die Hälfte der Steinplatten, auf denen etwa ein Drittel aller Schriftzeichen eingraviert ist, angefertigt wurde. Durch eine detaillierte Analyse der Kolophone dieser Zeit werden nicht nur Arbeitsprozesse und Hintergründe des Projekts beleuchtet, die Kolophone geben auch seltene Einblicke in Politik, Gesellschaft und Buddhismus der Liao sowie in das Verhältnis zwischen den herrschenden Kitan und der Han-chinesischen Bevölkerung dieser Region. Das Werk, das auch aktuelle archäologische Funde aus dem Nordosten Chinas berücksichtigt, stellt eine wichtige Ergänzung zur politischen, sozialen und kulturellen Geschichte der Liao-Dynastie dar.