Intelligent Systems And Robotics / Edition 1 available in Hardcover
- Pub. Date:
- Taylor & Francis
Intelligent Systems and Robotics focuses on new developments in robotics and intelligent systems and provides insight, guidance and specific techniques vital to those concerned with the design and implementation of robotics and intelligent system applications. Intelligent Systems and Robotics presents information on a 3-D vision for robots and intelligent control of a vision-based reasoning system with a robot manipulator. The reader will find authoritative presentations on autonomous land vehicle navigation, manipulator reachable workspace problems and the formulation of algorithms for their solution. Covered are methods for medical applications utilizing expert adaptive control, the integrated piezoelectric sensor/actuator design for distributed identification and control of smart machines, including theory, experiments, finite element formulation and analysis. Automatic repair of aircraft transparencies and geometric modeling utilized in robot task planning as well as the evaluation of standard fieldbus networks utilized in the factory environment are presented.
|Publisher:||Taylor & Francis|
|Product dimensions:||6.00(w) x 9.00(h) x 1.00(d)|
Table of Contents
1. Detection of Low-Contrast Road Edges for Automous Land Vehicle Navigation 2. Formulation and Algorithms for Solving the Manipulator Reachable Work Space Problems 3. Expert Adaptive Control: Method and Medical Application 4. Integrated Piezoelectric Sensor/Actuator Design for Distributed Identification and Control of Smart Machines and Flexible Robots Part 1: Theory and Experiments 5. Integrated Piezoelectric Sensor/Actuator Design for Distributed Identification and Control of Smart Machines and Flexible Robots Part 2: Finite Element Formulation and Analysis 6. Automated Repair of Aircraft Transparencies 7. Geometric Modeling for Robot Task Planning 8.
Evolution of Standard Fieldbus Networks 9. Triangle-Based Surface Models 10. Representation and Conversion Issues in Solid Modeling