Fusion’99 Plenary Speech
Multisensor Fusion and
Integration Issues, Approaches and Opportunities
ABSTRACT
Dr. Ren C. Luo
Professor and Dean
College of Engineering
National Chung Cheng University,
Chia-Yi, Taiwan, R.O.C.
Interest has been growing in the use of
multiple sensors to increase the capability of intelligent system. In this presentation,
the issues, approaches in dealing with multisensor fusion and integration (MFI) will be
discussed. The applications and potential opportunities for the implementation of MFI will
also be included. The issues involved in integrating multiple sensors into the operation
of a system are presented in the context of the type of information these sensors can
uniquely provide. The advantages gained through the synergistic use of multisensory
information can be decomposed into a combination of four fundamental aspects: the
redundancy, complementarily, timeliness, and cost of the information can then defined as
the degree to which each of these four aspects is present in the information provided by
the sensors.
In general, sensory fusion can be accomplished at
different levels: data fusion, feature fusion and decision fusion. More commonly known is
data fusion level, Example of this type of fusion are fusion of multiple ultrasonic data,
and fusion of images from different imaging sensors. In feature fusion level, features are
extracted from the raw measurements that are then combined in a quantitative or
qualitative manner. For example, feature fusion can be used to fuse information from
imaging and a non-imaging sensor. Decision fusion level can be employed when the sensors
available are not compatible or be applicable to many pattern recognition problems.
Typical of the applications that can benefit from
the use of multiple sensors are industrial tasks like assembly, military command and
control for battlefield management, mobile robot navigation, multitarget tracking, and
aircraft navigation. Common among all of these applications is the requirement that the
systems intelligently interact with and operate in an unstructured environment without the
complete control of a human operator. Advances in hardware, software and algorithm have
made it possible to employ multiple data sources for information gathering and to develop
more complex multisensor fusion and integration system. An example of applying MFI system
in an automations mobile robot/intelligent wheelchair system with video demonstration will
also be presented.
Biographical Sketch – Dr. Ren C. Luo
Ren C. Luo (IEEE
M’82 – SM’87 – F’92), is currently a Professor and Dean of
College of Engineering at National Chung Cheng University, he also served as Director of
Automation Technologies Program at National Science Council and Advisor of Ministry of
Economics Affairs in Taiwan, R.O.C. He was a Professor in the Department of Electrical and
Computer Engineering and the Director of the Center for Robotics and Intelligent Machines
at North Carolina State University in Raleigh, North Carolina, USA. He received his Ph.D
degrees from Technische Universitaet Berlin, Berlin, Germany in 1982.
From
1983 to 1984, he was an Assistant Professor in the Department of Electrical Engineering
and Computer Science at the University of Illinois at Chicago. From 1984 to 1990, he was
Assistant, Associate Professor and became Professor since 1991 in the Department of
Electrical Computer Engineering at North Carolina State University, Raleigh, NC. From 1992
to 1993, he was Toshiba Chair Professor at University of Tokyo, Japan.
Dr. Luo’s
research interests include: sensor-based intelligent robotics systems, multisensor fusion
and integration, computer vision, rapid prototyping and advanced manufacturing systems.
Dr. Luo has published over 170 technical journals, proceedings, and patents in the
above-mentioned areas. He authored a book, Multisensor Fusion and Integration
(Ablex, 1995); and was editor of the book, Robotics and Vision (IEEE, 1988). Dr.
Luo was also guest editors for the Journal of Robotics Systems (John Wiley & Sons.
Vol. 7, #3, 1990), IEEE Transactions on Industrial Electronics in special issues on the
topics of multisensor fusion and integration for intelligent machines, and editor of
IEEE/ASME Transactions on Mechatronics.
Dr. Luo currently
serves as President-Elect of IEEE Industrial Electronics Society and also serves as
Technical Council Chairman of Mechatronics in the same Society; and as Technical Committee
Chair on Multisensor Fusion of IEEE Robotics and Automation Society, Associate Editor of
IEEE Transaction on Industrial Electronics and IEEE Transactions on Control System
Technology. He contributes regularly to conferences, workshops, symposiums on program
committees and offering short courses or tutorials and plenary speeches in various
countries and research communities.
Dr. Luo has received
ALCOA Foundation Distinguished Engineering Research Award at North Carolina State
University. He also received IEEE Eugean Mittleman Outstanding Research Achievement Award.
He and his students have won twice Championship for the AAAI (American Association of
Artificial Intelligence) sponsored International Robots Competition in 1993 and 1995
respectively.
Dr. Luo was
Technical Program Chair of IEEE International Conference on Intelligent Motion Control
(Istanbul, Turkey, 1989). He was General Chair of the International Conference on
Intelligent Robots and Systems (IROS’92, Jointly sponsored by IEEE and Robotics
Society of Japan (RSJ), in Raleigh, NC, USA, July 1992). He was the General Chairman of
the 1994 IEEE International Conference on Multisensor Fusion and Integration for
Intelligent System (MFI’94) jointly with RSJ in Las Vegas, NV, USA). He was the
General Chairman of the 1996 IEEE International Conference on Industrial Electronics
(IECON’96 in Taipei, Taiwan, R.O.C.). His professional society memberships include:
IEEE’s Industrial Electronic Society, Robotics and Automation Society and Computer
Society; Verein Deutscher Ingenieur (VDI), Robotics Society of Japan (RSJ), Society of
Manufacturing Engineers (SME). Dr. Luo is Fellow of IEEE.
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