Sensor Fusion and Decentralized Control in Robotic Systems
Author | : |
Publisher | : |
Total Pages | : 272 |
Release | : 2001 |
Genre | : Autonomous robots |
ISBN | : |
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Author | : |
Publisher | : |
Total Pages | : 272 |
Release | : 2001 |
Genre | : Autonomous robots |
ISBN | : |
Author | : Paul S. Schenker |
Publisher | : SPIE-International Society for Optical Engineering |
Total Pages | : 344 |
Release | : 1997 |
Genre | : Technology & Engineering |
ISBN | : |
Author | : G. T. McKee |
Publisher | : SPIE-International Society for Optical Engineering |
Total Pages | : 352 |
Release | : 1999 |
Genre | : Technology & Engineering |
ISBN | : |
This work presents a series of papers examining various aspects of sensor fusion and decentralized control in robotic systems.
Author | : Paul S. Schenker |
Publisher | : |
Total Pages | : |
Release | : 1998-10 |
Genre | : Technology & Engineering |
ISBN | : 9780819429841 |
Author | : G. T. McKee |
Publisher | : Society of Photo Optical |
Total Pages | : 486 |
Release | : 2000 |
Genre | : Technology & Engineering |
ISBN | : 9780819438614 |
Author | : G. T. McKee |
Publisher | : Society of Photo Optical |
Total Pages | : 250 |
Release | : 2001 |
Genre | : Technology & Engineering |
ISBN | : 9780819442994 |
Author | : |
Publisher | : |
Total Pages | : 508 |
Release | : 2000 |
Genre | : Autonomous robots |
ISBN | : |
Author | : Arthur G.O. Mutambara |
Publisher | : Routledge |
Total Pages | : 252 |
Release | : 2019-05-20 |
Genre | : Technology & Engineering |
ISBN | : 1351456490 |
Decentralized Estimation and Control for Multisensor Systems explores the problem of developing scalable, decentralized estimation and control algorithms for linear and nonlinear multisensor systems. Such algorithms have extensive applications in modular robotics and complex or large scale systems, including the Mars Rover, the Mir station, and Space Shuttle Columbia. Most existing algorithms use some form of hierarchical or centralized structure for data gathering and processing. In contrast, in a fully decentralized system, all information is processed locally. A decentralized data fusion system includes a network of sensor nodes - each with its own processing facility, which together do not require any central processing or central communication facility. Only node-to-node communication and local system knowledge are permitted. Algorithms for decentralized data fusion systems based on the linear information filter have been developed, obtaining decentrally the same results as those in a conventional centralized data fusion system. However, these algorithms are limited, indicating that existing decentralized data fusion algorithms have limited scalability and are wasteful of communications and computation resources. Decentralized Estimation and Control for Multisensor Systems aims to remove current limitations in decentralized data fusion algorithms and to extend the decentralized principle to problems involving local control and actuation. The text discusses: Generalizing the linear Information filter to the problem of estimation for nonlinear systems Developing a decentralized form of the algorithm Solving the problem of fully connected topologies by using generalized model distribution where the nodal system involves only locally relevant states Reducing computational requirements by using smaller local model sizes Defining internodal communication Developing estima
Author | : Ramon Garcia-Hernandez |
Publisher | : Springer |
Total Pages | : 121 |
Release | : 2017-02-05 |
Genre | : Technology & Engineering |
ISBN | : 3319533126 |
This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network. The third control scheme applies a decentralized neural inverse optimal control for stabilization. The fourth decentralized neural inverse optimal control is designed for trajectory tracking. This comprehensive work on decentralized control of robot manipulators and mobile robots is intended for professors, students and professionals wanting to understand and apply advanced knowledge in their field of work.
Author | : James Manyika |
Publisher | : Prentice Hall |
Total Pages | : 304 |
Release | : 1994 |
Genre | : Technology & Engineering |
ISBN | : |
Presenting a single probability-based information-theoretic model for addressing issues in data fusion and sensor management for multi-sensor systems in general and decentralized systems in particular, this text develops mutually consistent data fusion architectures and algorithms. The algorithms are various architectural forms of the information filter and a corresponding Bayesian classification algorithm. Of significance is the normative sensor management method, making use of information-based utility functions.