Buch, Englisch, Band 47, 526 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 2060 g
Selected Contributions of the Seventh International Workshop on the Algorithmic Foundations of Robotics
Buch, Englisch, Band 47, 526 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 2060 g
Reihe: Springer Tracts in Advanced Robotics
ISBN: 978-3-540-68404-6
Verlag: Springer Berlin Heidelberg
This book contains the proceedings from the 2006 Workshop on the Algorithmic Foundations of Robotics. This biannual workshop is a highly selective meeting of leading researchers in the field of algorithmic issues related to robotics. The 32 papers in this book span a wide variety of topics: from fundamental motion planning algorithms to applications in medicine and biology, but they have in common a foundation in the algorithmic problems of robotic systems.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau Triebwerkstechnik, Energieübertragung
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie
- Mathematik | Informatik Mathematik Mathematische Analysis Variationsrechnung
Weitere Infos & Material
Probabilistic Roadmap Methods (PRMs).- Quantitative Analysis of Nearest-Neighbors Search in High-Dimensional Sampling-Based Motion Planning.- Path Deformation Roadmaps.- Workspace-Based Connectivity Oracle: An Adaptive Sampling Strategy for PRM Planning.- Incremental Map Generation (IMG).- Planning for Movable and Moving Obstacles.- Caging Polygons with Two and Three Fingers.- An Effective Framework for Path Planning Amidst Movable Obstacles.- Planning the Shortest Safe Path Amidst Unpredictably Moving Obstacles.- Planning Among Movable Obstacles with Artificial Constraints.- Navigation, SLAM, and Error Models for Filtering/Control.- Inferring and Enforcing Relative Constraints in SLAM.- Second-Order Theory of Error Propagation on Motion Groups.- Extensive Representations and Algorithms for Nonlinear Filtering and Estimation.- Geometric Computations and Applications.- An Experimental Study of Weighted k-Link Shortest Path Algorithms.- Low-Discrepancy Curves and Efficient Coverage of Space.- The Snowblower Problem.- Stratified Deformation Space and Path Planning for a Planar Closed Chain with Revolute Joints.- Motion Planning.- Competitive Disconnection Detection in On-Line Mobile Robot Navigation.- A Simple Path Non-existence Algorithm Using C-Obstacle Query.- RESAMPL: A Region-Sensitive Adaptive Motion Planner.- Motion Planning for a Six-Legged Lunar Robot.- Applications in Medicine and Biology.- Constant-Curvature Motion Planning Under Uncertainty with Applications in Image-Guided Medical Needle Steering.- Extended Abstract: Structure Determination of Symmetric Protein Complexes by a Complete Search of Symmetry Configuration Space Using NMR Distance Restraints.- Control and Planning for Mechanical Systems.- The Minimum-Time Trajectories for an Omni-DirectionalVehicle.- Mechanical Manipulation Using Reduced Models of Uncertainty.- Motion Planning for Variable Inertia Mechanical Systems.- Sampling-Based Falsification and Verification of Controllers for Continuous Dynamic Systems.- Sensor Networks and Reconfiguration.- Surrounding Nodes in Coordinate-Free Networks.- Passive Mobile Robot Localization within a Fixed Beacon Field.- Efficient Motion Planning Strategies for Large-Scale Sensor Networks.- Asymptotically Optimal Kinodynamic Motion Planning for Self-reconfigurable Robots.- Planning for Games, VR, and Humanoid Motion.- Visibility-Based Pursuit-Evasion with Bounded Speed.- Planning Near-Optimal Corridors Amidst Obstacles.- Using Motion Primitives in Probabilistic Sample-Based Planning for Humanoid Robots.