Multisensor Integration and Fusion for Intelligent Machines and Systems PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Multisensor Integration and Fusion for Intelligent Machines and Systems PDF full book. Access full book title Multisensor Integration and Fusion for Intelligent Machines and Systems by Ren C. Luo. Download full books in PDF and EPUB format.
Author: Ren C. Luo Publisher: Intellect Books ISBN: Category : Computers Languages : en Pages : 736
Book Description
There has been a growing interest during the 1990s in the use of multiple sensors to increase the capabilities of intelligent machines and systems. This text is a compendium of some of the most important and influential work that has appeared in this area. In addition, it contains comprehensive introductory material and an extensive survey and review of related research. The volume should be useful to everyone interested in the development of more intelligent machines and systems through the synergistic use of multiple sensors.
Author: Ren C. Luo Publisher: Intellect Books ISBN: Category : Computers Languages : en Pages : 736
Book Description
There has been a growing interest during the 1990s in the use of multiple sensors to increase the capabilities of intelligent machines and systems. This text is a compendium of some of the most important and influential work that has appeared in this area. In addition, it contains comprehensive introductory material and an extensive survey and review of related research. The volume should be useful to everyone interested in the development of more intelligent machines and systems through the synergistic use of multiple sensors.
Author: Lee Suk-han Publisher: Springer Science & Business Media ISBN: 354089859X Category : Technology & Engineering Languages : en Pages : 476
Book Description
The ?eld of multi-sensor fusion and integration is growing into signi?cance as our societyisintransitionintoubiquitouscomputingenvironmentswithroboticservices everywhere under ambient intelligence. What surround us are to be the networks of sensors and actuators that monitor our environment, health, security and safety, as well as the service robots, intelligent vehicles, and autonomous systems of ever heightened autonomy and dependability with integrated heterogeneous sensors and actuators. The ?eld of multi-sensor fusion and integration plays key role for m- ing the above transition possible by providing fundamental theories and tools for implementation. This volume is an edition of the papers selected from the 7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI‘08, held in Seoul, Korea, August 20–22, 2008. Only 32 papers out of the 122 papers accepted for IEEE MFI’08 were chosen and requested for revision and extension to be included in this volume. The 32 contributions to this volume are organized into three parts: Part I is dedicated to the Theories in Data and Information Fusion, Part II to the Multi-Sensor Fusion and Integration in Robotics and Vision, and Part III to the Applications to Sensor Networks and Ubiquitous Computing Environments. To help readers understand better, a part summary is included in each part as an introduction. The summaries of Parts I, II, and III are prepared respectively by Prof. Hanseok Ko, Prof. Sukhan Lee and Prof. Hernsoo Hahn.
Author: Lee Suk-han Publisher: Springer ISBN: 9783540898580 Category : Technology & Engineering Languages : en Pages : 479
Book Description
The ?eld of multi-sensor fusion and integration is growing into signi?cance as our societyisintransitionintoubiquitouscomputingenvironmentswithroboticservices everywhere under ambient intelligence. What surround us are to be the networks of sensors and actuators that monitor our environment, health, security and safety, as well as the service robots, intelligent vehicles, and autonomous systems of ever heightened autonomy and dependability with integrated heterogeneous sensors and actuators. The ?eld of multi-sensor fusion and integration plays key role for m- ing the above transition possible by providing fundamental theories and tools for implementation. This volume is an edition of the papers selected from the 7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI‘08, held in Seoul, Korea, August 20–22, 2008. Only 32 papers out of the 122 papers accepted for IEEE MFI’08 were chosen and requested for revision and extension to be included in this volume. The 32 contributions to this volume are organized into three parts: Part I is dedicated to the Theories in Data and Information Fusion, Part II to the Multi-Sensor Fusion and Integration in Robotics and Vision, and Part III to the Applications to Sensor Networks and Ubiquitous Computing Environments. To help readers understand better, a part summary is included in each part as an introduction. The summaries of Parts I, II, and III are prepared respectively by Prof. Hanseok Ko, Prof. Sukhan Lee and Prof. Hernsoo Hahn.
Author: Lee Suk-han Publisher: Springer ISBN: 9783540898603 Category : Technology & Engineering Languages : en Pages : 479
Book Description
The ?eld of multi-sensor fusion and integration is growing into signi?cance as our societyisintransitionintoubiquitouscomputingenvironmentswithroboticservices everywhere under ambient intelligence. What surround us are to be the networks of sensors and actuators that monitor our environment, health, security and safety, as well as the service robots, intelligent vehicles, and autonomous systems of ever heightened autonomy and dependability with integrated heterogeneous sensors and actuators. The ?eld of multi-sensor fusion and integration plays key role for m- ing the above transition possible by providing fundamental theories and tools for implementation. This volume is an edition of the papers selected from the 7th IEEE International Conference on Multi-Sensor Integration and Fusion, IEEE MFI‘08, held in Seoul, Korea, August 20–22, 2008. Only 32 papers out of the 122 papers accepted for IEEE MFI’08 were chosen and requested for revision and extension to be included in this volume. The 32 contributions to this volume are organized into three parts: Part I is dedicated to the Theories in Data and Information Fusion, Part II to the Multi-Sensor Fusion and Integration in Robotics and Vision, and Part III to the Applications to Sensor Networks and Ubiquitous Computing Environments. To help readers understand better, a part summary is included in each part as an introduction. The summaries of Parts I, II, and III are prepared respectively by Prof. Hanseok Ko, Prof. Sukhan Lee and Prof. Hernsoo Hahn.
Author: Sukhan Lee Publisher: Springer ISBN: 3319905090 Category : Technology & Engineering Languages : en Pages : 300
Book Description
This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16–22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.
Author: Dhiral Laxmichand Chheda Publisher: ISBN: Category : Languages : en Pages : 386
Book Description
The philosophy of research at the University of Texas -- Robotics Research Group (RRG) is towards creating a foundation for an open architecture, reconfigurable intelligent machines to meet wide breadth of operational needs. An intelligent system is the one which has complete knowledge of its operating characteristics at all times (updated in real-time) and it can make on-the-fly decisions to adapt itself to the different conditions or present the best possible options to the human decision maker under specified and ranked criteria. The reality of all complex system is that they are inherently non-linear with coupled parameters. The traditional approach dealing with such systems assumes linearized models, imposing conservative bounds on the operational domain and thus limiting performance capability of the system. Recent advancements in sensor technology and availability of computational resources (embedded processing) at low cost have made real-time intelligent control feasible for complex systems. The computational intelligence envisioned in modern intelligent machines will enhance the system performance and will provide capabilities such as criteria based control, identification of incipient faults, condition based maintenance, fault tolerance, and ability to monitor performance parameters in real-time. The first step in this process is to equip a system with a comprehensive suite of sensors. These sensors will provide real-time data and awareness about both, the internal system states and the external/environmental operating conditions. The aim of this work is to establish an argument in favor of using multiple sensors in all complex electro-mechanical systems. The report discusses numerous benefits of a multi-sensor environment with suitable examples and attempts to justify its pressing need in all the existing complex mechanical systems. Case studies for a multi-sensor environment in railroad freight cars and vehicle systems are presented. Sensing requirements in freight train and vehicle systems are evaluated and suitable sensor technology and commercial sensor options are suggested for decision makers. In addition to benefits, challenges in a multi-sensor environment such as sensor noise, cabling complexities, signal processing, communication, data validation and data management, sensor fusion, information integration, maintenance etc. are addressed and best practices to alleviate these complexities are discussed in the report. This effort lays out a foundation for developing a multi-sensor system and will enable computational intelligence and structured decision making in the system.
Author: Bozzano G Luisa Publisher: Academic Press ISBN: 0323138357 Category : Computers Languages : en Pages : 559
Book Description
This book addresses the techniques for modeling and integration of data provided by different sensors within robotics and knowledge sources within machine intelligence. Leaders in robotics and machine intelligence capture state-of-the-art technology in data sensor fusion and give a unified vision of the future of the field, presented from both the theoretical and practical angles.
Author: Rajive Joshi Publisher: World Scientific ISBN: 9789810238803 Category : Science Languages : en Pages : 340
Book Description
The fusion of information from sensors with different physical characteristics, such as sight, touch, sound, etc., enhances the understanding of our surroundings and provides the basis for planning, decision-making, and control of autonomous and intelligent machines. The minimal representation approach to multisensor fusion is based on the use of an information measure as a universal yardstick for fusion. Using models of sensor uncertainty, the representation size guides the integration of widely varying types of data and maximizes the information contributed to a consistent interpretation. In this book, the general theory of minimal representation multisensor fusion is developed and applied in a series of experimental studies of sensor-based robot manipulation. A novel application of differential evolutionary computation is introduced to achieve practical and effective solutions to this difficult computational problem.
Author: Rajive Joshi Publisher: World Scientific ISBN: 9814494798 Category : Technology & Engineering Languages : en Pages : 336
Book Description
The fusion of information from sensors with different physical characteristics, such as sight, touch, sound, etc., enhances the understanding of our surroundings and provides the basis for planning, decision-making, and control of autonomous and intelligent machines.The minimal representation approach to multisensor fusion is based on the use of an information measure as a universal yardstick for fusion. Using models of sensor uncertainty, the representation size guides the integration of widely varying types of data and maximizes the information contributed to a consistent interpretation.In this book, the general theory of minimal representation multisensor fusion is developed and applied in a series of experimental studies of sensor-based robot manipulation. A novel application of differential evolutionary computation is introduced to achieve practical and effective solutions to this difficult computational problem.
Author: Ren C. Luo
Author: Ren C. Luo
Author: Lee Suk-han
Author: Lee Suk-han
Author: Lee Suk-han
Author: Sukhan Lee
Author: Dhiral Laxmichand Chheda
Author: Bozzano G Luisa
Author: Rajive Joshi
Author: 
Author: Rajive Joshi