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Cluster computing for robotics and computer vision [[electronic resource] /] / Damian M. Lyons
| Cluster computing for robotics and computer vision [[electronic resource] /] / Damian M. Lyons |
| Autore | Lyons Damian M |
| Pubbl/distr/stampa | Singapore, : World Scientific, c2011 |
| Descrizione fisica | 1 online resource (235 p.) |
| Disciplina | 629.8925 |
| Soggetto topico |
Robotics - Programming
Computer vision - Programming |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-43325-7
9786613433251 981-283-636-5 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Dedication; Preface; Contents; List of Tables; List of Figures; 1. Introduction; 1.1 Robots; 1.2 Cluster Computing; 1.3 Overview of the Book; 2. Clusters and Robots; 2.1 Parallel Computation; 2.1.1 Parallel Architectures; 2.1.2 Multiprocessor; 2.1.3 Multicomputer; 2.2 Clusters; 2.2.1 Terminology; 2.2.2 Cluster Configuration; 2.2.3 Programming the Cluster; 2.2.4 Configuring the Cluster; 2.2.5 Simple Cluster Configuration with OpenMPI; 2.2.6 Connecting the Cluster to the Robot; 2.3 Summary; References; 3. Cluster Programming; 3.1 Approaches to Parallel Programming; 3.2 Programming with MPI
3.2.1 Message-Passing3.2.2 Single Program Multiple Data (SPMD) Model; 3.2.3 Collective Communication; 3.3 Compiling and Running MPI Programs; 3.4 Analyzing Parallel Computation Time; 3.4.1 Speedup and Amdhal'sLaw; 3.4.2 Communication and Calculation; 3.4.3 Communication Models; 3.5 Summary; References; 4. Robot Motion; 4.1 Motion of a Mobile Robot in Two Dimensions; 4.2 Calculation of Location by Dead-Reckoning; 4.2.1 Partitioning: Block Data Decomposition; 4.2.2 Program Design; 4.2.3 Analysis; 4.3 Dead-Reckoning with Intermediate Results; 4.3.1 Partitioning; 4.3.2 Program Design 4.3.3 Analysis4.4 Dead-Reckoning for a Team of Robots; 4.4.1 Partitioning; 4.4.2 Program Design; 4.4.3 Analysis; 4.4.4 Local and Global Buffers; 4.5 Summary; References; 5. Sensors; 5.1 Transforming Sensor Readings; 5.1.1 Partitioning: Single Robot Location; 5.1.2 Analysis; 5.1.3 Partitioning: Multiple Robot Locations; 5.1.4 Analysis; 5.2 Drawing a Map from Sonar Data; 5.2.1 Finding Straight Lines with the Hough Transform; 5.2.2 Partitioning; 5.2.3 Program Design; 5.2.4 Analysis; 5.2.5 Load Balanced Hough Calculation; 5.2.6 Analysis; 5.3 Aligning Laser Scan Measurements 5.3.1 Polar Scan Matching5.3.2 Partitioning and Analysis; 5.3.3 Program Design; 5.4 Summary; References; 6. Mapping and Localization; 6.1 Constructing a Spatial Occupancy Map; 6.1.1 Probabilistic Sonar Model; 6.1.2 Bayesian Filtering; 6.1.3 Partitioning by Map; 6.1.4 Program Design; 6.1.4.1. Phase 1; 6.1.4.2. Phase 2; 6.1.4.3. Phase 3; 6.1.4.4. Phase 4; 6.1.5 Analysis; 6.1.6 Partitioning by Sensor Readings; 6.1.7 Program Design; 6.1.8 Analysis; 6.2 Monte-Carlo Localization; 6.2.1 Partitioning; 6.2.2 Program Design; 6.2.3 Analysis; 6.2.4 Improving the Serial Fraction; 6.3 Summary; References 7. Vision and Tracking7.1 Following the Road; 7.2 Iconic Image Processing; 7.2.1 Partitioning; 7.2.2 Program Design; 7.2.3 Analysis; 7.2.4 Spatial Pixel Operations; 7.2.5 Partitioning; 7.2.6 Program Design; 7.3 Multiscale Image Processing; 7.3.1 Partitioning; 7.4 Video Tracking; 7.4.1 Spatial Histograms; 7.4.2 Condensation; 7.4.3 Partitioning; 7.4.4 Program Design; 7.5 Summary; References; 8. Learning Landmarks; 8.1 Landmark Spatiograms; 8.2 K-Means Clustering; 8.2.1 Partitioning; 8.2.2 Program Design; 8.2.3 Analysis; 8.3 EM Clustering; 8.3.1 Partitioning; 8.3.2 Program Design; 8.3.3 Analysis 8.4 Summary |
| Record Nr. | UNINA-9910457458803321 |
Lyons Damian M
|
||
| Singapore, : World Scientific, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Cluster computing for robotics and computer vision [[electronic resource] /] / Damian M. Lyons
| Cluster computing for robotics and computer vision [[electronic resource] /] / Damian M. Lyons |
| Autore | Lyons Damian M |
| Pubbl/distr/stampa | Singapore, : World Scientific, c2011 |
| Descrizione fisica | 1 online resource (235 p.) |
| Disciplina | 629.8925 |
| Soggetto topico |
Robotics - Programming
Computer vision - Programming |
| ISBN |
1-283-43325-7
9786613433251 981-283-636-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Dedication; Preface; Contents; List of Tables; List of Figures; 1. Introduction; 1.1 Robots; 1.2 Cluster Computing; 1.3 Overview of the Book; 2. Clusters and Robots; 2.1 Parallel Computation; 2.1.1 Parallel Architectures; 2.1.2 Multiprocessor; 2.1.3 Multicomputer; 2.2 Clusters; 2.2.1 Terminology; 2.2.2 Cluster Configuration; 2.2.3 Programming the Cluster; 2.2.4 Configuring the Cluster; 2.2.5 Simple Cluster Configuration with OpenMPI; 2.2.6 Connecting the Cluster to the Robot; 2.3 Summary; References; 3. Cluster Programming; 3.1 Approaches to Parallel Programming; 3.2 Programming with MPI
3.2.1 Message-Passing3.2.2 Single Program Multiple Data (SPMD) Model; 3.2.3 Collective Communication; 3.3 Compiling and Running MPI Programs; 3.4 Analyzing Parallel Computation Time; 3.4.1 Speedup and Amdhal'sLaw; 3.4.2 Communication and Calculation; 3.4.3 Communication Models; 3.5 Summary; References; 4. Robot Motion; 4.1 Motion of a Mobile Robot in Two Dimensions; 4.2 Calculation of Location by Dead-Reckoning; 4.2.1 Partitioning: Block Data Decomposition; 4.2.2 Program Design; 4.2.3 Analysis; 4.3 Dead-Reckoning with Intermediate Results; 4.3.1 Partitioning; 4.3.2 Program Design 4.3.3 Analysis4.4 Dead-Reckoning for a Team of Robots; 4.4.1 Partitioning; 4.4.2 Program Design; 4.4.3 Analysis; 4.4.4 Local and Global Buffers; 4.5 Summary; References; 5. Sensors; 5.1 Transforming Sensor Readings; 5.1.1 Partitioning: Single Robot Location; 5.1.2 Analysis; 5.1.3 Partitioning: Multiple Robot Locations; 5.1.4 Analysis; 5.2 Drawing a Map from Sonar Data; 5.2.1 Finding Straight Lines with the Hough Transform; 5.2.2 Partitioning; 5.2.3 Program Design; 5.2.4 Analysis; 5.2.5 Load Balanced Hough Calculation; 5.2.6 Analysis; 5.3 Aligning Laser Scan Measurements 5.3.1 Polar Scan Matching5.3.2 Partitioning and Analysis; 5.3.3 Program Design; 5.4 Summary; References; 6. Mapping and Localization; 6.1 Constructing a Spatial Occupancy Map; 6.1.1 Probabilistic Sonar Model; 6.1.2 Bayesian Filtering; 6.1.3 Partitioning by Map; 6.1.4 Program Design; 6.1.4.1. Phase 1; 6.1.4.2. Phase 2; 6.1.4.3. Phase 3; 6.1.4.4. Phase 4; 6.1.5 Analysis; 6.1.6 Partitioning by Sensor Readings; 6.1.7 Program Design; 6.1.8 Analysis; 6.2 Monte-Carlo Localization; 6.2.1 Partitioning; 6.2.2 Program Design; 6.2.3 Analysis; 6.2.4 Improving the Serial Fraction; 6.3 Summary; References 7. Vision and Tracking7.1 Following the Road; 7.2 Iconic Image Processing; 7.2.1 Partitioning; 7.2.2 Program Design; 7.2.3 Analysis; 7.2.4 Spatial Pixel Operations; 7.2.5 Partitioning; 7.2.6 Program Design; 7.3 Multiscale Image Processing; 7.3.1 Partitioning; 7.4 Video Tracking; 7.4.1 Spatial Histograms; 7.4.2 Condensation; 7.4.3 Partitioning; 7.4.4 Program Design; 7.5 Summary; References; 8. Learning Landmarks; 8.1 Landmark Spatiograms; 8.2 K-Means Clustering; 8.2.1 Partitioning; 8.2.2 Program Design; 8.2.3 Analysis; 8.3 EM Clustering; 8.3.1 Partitioning; 8.3.2 Program Design; 8.3.3 Analysis 8.4 Summary |
| Record Nr. | UNINA-9910778807503321 |
|
Lyons Damian M
|
||
| Singapore, : World Scientific, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Cluster computing for robotics and computer vision [[electronic resource] /] / Damian M. Lyons
| Cluster computing for robotics and computer vision [[electronic resource] /] / Damian M. Lyons |
| Autore | Lyons Damian M |
| Pubbl/distr/stampa | Singapore, : World Scientific, c2011 |
| Descrizione fisica | 1 online resource (235 p.) |
| Disciplina | 629.8925 |
| Soggetto topico |
Robotics - Programming
Computer vision - Programming |
| ISBN |
1-283-43325-7
9786613433251 981-283-636-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Dedication; Preface; Contents; List of Tables; List of Figures; 1. Introduction; 1.1 Robots; 1.2 Cluster Computing; 1.3 Overview of the Book; 2. Clusters and Robots; 2.1 Parallel Computation; 2.1.1 Parallel Architectures; 2.1.2 Multiprocessor; 2.1.3 Multicomputer; 2.2 Clusters; 2.2.1 Terminology; 2.2.2 Cluster Configuration; 2.2.3 Programming the Cluster; 2.2.4 Configuring the Cluster; 2.2.5 Simple Cluster Configuration with OpenMPI; 2.2.6 Connecting the Cluster to the Robot; 2.3 Summary; References; 3. Cluster Programming; 3.1 Approaches to Parallel Programming; 3.2 Programming with MPI
3.2.1 Message-Passing3.2.2 Single Program Multiple Data (SPMD) Model; 3.2.3 Collective Communication; 3.3 Compiling and Running MPI Programs; 3.4 Analyzing Parallel Computation Time; 3.4.1 Speedup and Amdhal'sLaw; 3.4.2 Communication and Calculation; 3.4.3 Communication Models; 3.5 Summary; References; 4. Robot Motion; 4.1 Motion of a Mobile Robot in Two Dimensions; 4.2 Calculation of Location by Dead-Reckoning; 4.2.1 Partitioning: Block Data Decomposition; 4.2.2 Program Design; 4.2.3 Analysis; 4.3 Dead-Reckoning with Intermediate Results; 4.3.1 Partitioning; 4.3.2 Program Design 4.3.3 Analysis4.4 Dead-Reckoning for a Team of Robots; 4.4.1 Partitioning; 4.4.2 Program Design; 4.4.3 Analysis; 4.4.4 Local and Global Buffers; 4.5 Summary; References; 5. Sensors; 5.1 Transforming Sensor Readings; 5.1.1 Partitioning: Single Robot Location; 5.1.2 Analysis; 5.1.3 Partitioning: Multiple Robot Locations; 5.1.4 Analysis; 5.2 Drawing a Map from Sonar Data; 5.2.1 Finding Straight Lines with the Hough Transform; 5.2.2 Partitioning; 5.2.3 Program Design; 5.2.4 Analysis; 5.2.5 Load Balanced Hough Calculation; 5.2.6 Analysis; 5.3 Aligning Laser Scan Measurements 5.3.1 Polar Scan Matching5.3.2 Partitioning and Analysis; 5.3.3 Program Design; 5.4 Summary; References; 6. Mapping and Localization; 6.1 Constructing a Spatial Occupancy Map; 6.1.1 Probabilistic Sonar Model; 6.1.2 Bayesian Filtering; 6.1.3 Partitioning by Map; 6.1.4 Program Design; 6.1.4.1. Phase 1; 6.1.4.2. Phase 2; 6.1.4.3. Phase 3; 6.1.4.4. Phase 4; 6.1.5 Analysis; 6.1.6 Partitioning by Sensor Readings; 6.1.7 Program Design; 6.1.8 Analysis; 6.2 Monte-Carlo Localization; 6.2.1 Partitioning; 6.2.2 Program Design; 6.2.3 Analysis; 6.2.4 Improving the Serial Fraction; 6.3 Summary; References 7. Vision and Tracking7.1 Following the Road; 7.2 Iconic Image Processing; 7.2.1 Partitioning; 7.2.2 Program Design; 7.2.3 Analysis; 7.2.4 Spatial Pixel Operations; 7.2.5 Partitioning; 7.2.6 Program Design; 7.3 Multiscale Image Processing; 7.3.1 Partitioning; 7.4 Video Tracking; 7.4.1 Spatial Histograms; 7.4.2 Condensation; 7.4.3 Partitioning; 7.4.4 Program Design; 7.5 Summary; References; 8. Learning Landmarks; 8.1 Landmark Spatiograms; 8.2 K-Means Clustering; 8.2.1 Partitioning; 8.2.2 Program Design; 8.2.3 Analysis; 8.3 EM Clustering; 8.3.1 Partitioning; 8.3.2 Program Design; 8.3.3 Analysis 8.4 Summary |
| Record Nr. | UNINA-9910822388803321 |
|
Lyons Damian M
|
||
| Singapore, : World Scientific, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||