Cover image for Robotic exploration and landmark determination : hardware-efficient algorithms and FPGA implementations
Title:
Robotic exploration and landmark determination : hardware-efficient algorithms and FPGA implementations
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Publication Information:
Berlin : Springer, 2008
Physical Description:
xiii, 137 p. : ill. ; 25 cm.
ISBN:
9783540753933
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30000010193019 TJ211 S74 2008 Open Access Book
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Summary

Summary

This book presents hardware-efficient algorithms and FPGA implementations for two robotic tasks, namely exploration and landmark determination. The work identifies scenarios for mobile robotics where parallel processing and selective shutdown offered by FPGAs are invaluable. The book proceeds to systematically develop memory-driven VLSI architectures for both the tasks. The architectures are ported to a low-cost FPGA with a fairly small number of system gates.


Table of Contents

Deniz Erdogmus and Umut Ozertem and Tian Lan&Obdot;d&eacbdot;túnjí Àjàdí &Obdot;D&eacbdot;l&obdot;BíStefan Scherer and Friedhelm Schwenker and Günther PalmK. Sreenivasa RaoGuo Chen and Vijay ParsaHemant A. Patil and T.K. BasuEnrique Alexandre and Lucas Cuadra and Manuel Rosa-Zurera and Francisco López-FerrerasPreeti RaoLeo Pape and Jornt de Gruijl and Marco WieringArvind Nayak and Subhasis Chaudhuri and Shilpa InamdarSusmita Ghosh and Swarnajyoti Patra and Ashish GhoshManjunath Aradhya V N and Hemantha Kumar G and Noushath SMiloÜ Oravec and Gregor Rozinaj and Marian BeszédeÜGustavo Camps-Valls and Antonio Rodrigo-GonzálezMatthew Browne and Saeed Shiry Ghidary and Norhert Michael MayerMayank Vatsa and Richa Singh and Afzel NoorePedro Rodrigues and Manuel Ferreira and João MonteiroSimona Ferrante and Alessandra Pedrocchi and Giancarlo Ferrigno
1 Introductionp. 3
1.1 Motivationp. 3
1.2 Addressing the Challengesp. 7
1.3 Architecture of an FPGA-based Robotp. 8
1.4 Contributions of this Researchp. 9
1.5 Organization of the Bookp. 11
2 Literature Surveyp. 13
2.1 Sensors and Processors for Mobile Robotsp. 13
2.2 Robotic Operation in Known and Unknown Environmentsp. 15
2.2.1 Environment with Prior Knowledge of Object Geometries and Locationsp. 15
2.2.2 Unknown Environmentsp. 16
2.3 FPGA-based Designp. 22
2.4 Summaryp. 23
3 Design and Development of an FPGA-based Robotp. 25
3.1 Motivationp. 25
3.2 Overall Structure of the Mobile Robotp. 26
3.3 Design of Ultrasonic Range Finderp. 28
3.4 Power Delivery to FPGA Board and Ultrasonic Range Findersp. 29
3.5 Logic Level Translatorp. 30
3.6 FPGA Boardp. 31
3.6.1 Interface Modulesp. 31
3.6.2 Pulse Width to Distance Converter (PWDC)p. 31
3.6.3 Universal Asynchronous Transmitter (UAT)p. 32
3.7 Description of Stepper Motor Interfacep. 32
3.8 Summaryp. 34
4 Hardware-Efficient Robotic Explorationp. 35
4.1 Introductionp. 35
4.2 Assumptions and Terminologyp. 36
4.3 The Proposed Algorithmp. 37
4.3.1 Key Ideasp. 37
4.3.2 Pseudo-Code for the Proposed Algorithmp. 39
4.4 The Proposed Architecture for FPGA-based Processingp. 44
4.4.1 Pulse Width to Distance Convertersp. 45
4.4.2 Content Addressable Memoryp. 45
4.4.3 Stack Memoryp. 47
4.4.4 Universal Asynchronous Transmitter (UAT)p. 47
4.4.5 Delay Elementp. 47
4.4.6 Adjacency Information Storing Memory Blocks: APX, APY, AMX and AMYp. 48
4.4.7 Memory Blocks Used for Map Construction: DPX, DPY, DMX, DMY, Visited Grid point_x and Grid point_yp. 48
4.4.8 Input Gating for Reducing Energy Consumptionp. 49
4.5 Experimental Resultsp. 50
4.6 General Remarks about Code and Demonstrationp. 59
4.7 Conclusionsp. 61
5 Hardware-Efficient Landmark Determinationp. 63
5.1 Motivation for Landmark Determinationp. 63
5.2 Assumptions and Terminologyp. 64
5.3 Proposed Algorithmp. 66
5.3.1 Key Ideasp. 66
5.3.2 The New Algorithmp. 68
5.4 The Proposed Architecturep. 71
5.4.1 Random Number Generationp. 72
5.4.2 Processing Element (PE) Structurep. 74
5.4.3 Global Memory Organisationp. 76
5.4.4 Content Addressable Memory (CAM)p. 77
5.4.5 Special Memoryp. 78
5.4.6 Adjacency Determination Unitp. 79
5.4.7 Input Gating for Reducing Energy Consumptionp. 81
5.5 FPGA Implementation Resultsp. 81
5.6 Summaryp. 86
6 The Road Aheadp. 87
6.1 Contributions of this Researchp. 87
6.2 Extensionsp. 88
6.2.1 Other Types of Mapsp. 88
6.2.2 Navigation in Dynamic Environmentsp. 88
6.2.3 Localization and other Tasksp. 90
6.3 Concluding Remarksp. 90
A Key Verilog Modules for Robotic Explorationp. 91
B Suggestions for Mini-Projectsp. 129
Referencesp. 133
Indexp. 139
Information Theoretic Feature Selection and Projectionp. 1
Recognition of Tones in YorÙbÁ Speech: Experiments With Artificial Neural Networksp. 23
Emotion Recognition from Speech Using Multi-Classifier Systems and RBF-Ensemblesp. 49
Modeling Supra-Segmental Features of Syllables Using Neural Networksp. 71
Objective Speech Quality Evaluation Using an Adaptive Neuro-Fuzzy Networkp. 97
A Novel Approach to Language Identification Using Modified Polynomial Networksp. 117
Speech/Non-Speech Classification in Hearing Aids Driven by Tailored Neural Networksp. 145
Audio Signal Processingp. 169
Democratic Liquid State Machines for Music Recognitionp. 191
Color Transfer and its Applicationsp. 217
A Neural Approach to Unsupervised Change Detection of Remote-Sensing Imagesp. 243
Fisher Linear Discriminant Analysis and Connectionist Model for Efficient Image Recognitionp. 269
Detection and Recognition of Human Faces and Facial Featuresp. 283
Classification of Satellite Images with Regularized AdaBoosting of RBF Neural Networksp. 307
Convolutional Neural Networks for Image Processing with Applications in Mobile Roboticsp. 327
SVM Based Adaptive Biometric Image Enhancement Using Quality Assessmentp. 351
Segmentation and Classification of Leukocytes Using Neural Networks: A Generalization Directionp. 373
A Closed Loop Neural Scheme to Control Knee Flex-Extension Induced by Functional Electrical Stimulation: Simulation Study and Experimental Test on a Paraplegic Subjectp. 397