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Robot Intelligence [electronic resource] : An Advanced Knowledge Processing Approach / edited by Honghai Liu, Dongbing Gu, Robert J. Howlett, Yonghuai Liu.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Advanced Information and Knowledge Processing | Advanced Information and Knowledge ProcessingEditor: London : Springer London : Imprint: Springer, 2010Descripción: XIV, 294 p. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9781849963299
Trabajos contenidos:
  • SpringerLink (Online service)
Tema(s): Formatos físicos adicionales: Sin títuloClasificación CDD:
  • 006.3 23
Clasificación LoC:
  • Q334-342
  • TJ210.2-211.495
Recursos en línea:
Contenidos:
Springer eBooksResumen: Robot Intelligence is an exciting interdisciplinary field including engineering, information technology, machine learning, biological science and psychology. Its dramatic growth in practical applications is driven by both real-world requirements and maturity of related disciplines such as intelligent algorithms. It is expected that perception, understanding and reasoning capabilities play a crucial role in robot-assisted tasks and enable robots to exhibit similar performance on executing various tasks in both constrained and unconstrained environments. Robot Intelligence is a rare collection of chapters reflecting recent robotics developments from the advanced knowledge processing perspective. It also provides a comprehensive introduction and methodology to selected robotics topics including human robot interaction, human motion analysis, robot vision and advanced control. The robot intelligence methods presented enable readers to address many complex problems involving a wide range of robot sensors for the perception and understanding of the environment and the reasoning of the subsequent actions. The books comprehensive coverage will prove invaluable to senior undergraduates, PhD students, researchers and practitioners.
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Programming-by-Demonstration of Robot Motions -- Grasp Recognition by Fuzzy Modeling andHidden Markov Models -- Distributed Adaptive Coordinated Control ofMulti-Manipulator Systems Using Neural Networks -- A New Framework for View-Invariant Human Action Recognition -- Using Fuzzy Gaussian Inference and Genetic Programming to Classify 3D Human Motions -- Obstacle Detection Using Cross-Ratio andDisparity Velocity -- Learning and Vision-Based Obstacle Avoidance and Navigation -- A Fraction Distortion Model for Accurate Camera Calibration and Correction -- A Leader-Follower Flocking System Based onEstimated Flocking Center -- A Behavior Based Control System forSurveillance UAVs -- Hierarchical Composite Anti-Disturbance Control for Robotic Systems Using Robust Disturbance Observer -- Autonomous Navigation for Mobile Robots withHuman-Robot Interaction -- Prediction-Based Perceptual System of a Partner Robot for Natural Communication.

Robot Intelligence is an exciting interdisciplinary field including engineering, information technology, machine learning, biological science and psychology. Its dramatic growth in practical applications is driven by both real-world requirements and maturity of related disciplines such as intelligent algorithms. It is expected that perception, understanding and reasoning capabilities play a crucial role in robot-assisted tasks and enable robots to exhibit similar performance on executing various tasks in both constrained and unconstrained environments. Robot Intelligence is a rare collection of chapters reflecting recent robotics developments from the advanced knowledge processing perspective. It also provides a comprehensive introduction and methodology to selected robotics topics including human robot interaction, human motion analysis, robot vision and advanced control. The robot intelligence methods presented enable readers to address many complex problems involving a wide range of robot sensors for the perception and understanding of the environment and the reasoning of the subsequent actions. The books comprehensive coverage will prove invaluable to senior undergraduates, PhD students, researchers and practitioners.

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