REN-CHYUAN LUO2020-06-162020-06-16198900189472https://scholars.lib.ntu.edu.tw/handle/123456789/502535https://www.scopus.com/inward/record.uri?eid=2-s2.0-0024737615&doi=10.1109%2f21.44007&partnerID=40&md5=6aa0fb899ec7a4eebcb1d0a7dc080330Interest has been growing in the use of multiple sensors to increase the capabilities of intelligent systems. 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 multi sensory information can be decomposed into a combination of four fundamental aspects: the redundancy, complementarity, timeliness, and cost of the information. The role of multiple sensors in the operation of a particular system can then be defined as the degree to which each of these four aspects is present in the information provided by the sensors. A distinction is made between multisensor integration and the more restricted notion of multi-sensor fusion to separate the more general issues involved in the integration of multiple sensory devices at the system architecture and control level, from the more specific issues-possibly mathematical or statistical-involved in the actual combination (or fusion) of multisensory information. A survey is provided of the increasing number and variety of approaches to the problem of multisensor integration and fusion that have appeared in the literature in recent years-ranging from general paradigms, frameworks, and methods for integrating and fusing multisensory information, to existing multisensor systems used in different areas of application. General multisensor fusion methods, sensor selection strategies, and world models are surveyed, along with approaches to the integration and fusion of information from combinations of different types of sensors. Short descriptions of the role of multisensor integration and fusion in the operation of a number of existing mobile robots are provided, together with proposed high-level multisensory representations suitable for mobile robot navigation and control. Existing multisensor systems are surveyed in the following areas of application: industrial tasks like material handling, part fabrication (e.g., welding), inspection, and assembly; military command and control for battle management; space; target tracking; inertial navigation; and the remote sensing of coastal waters. A discussion is included of possible problems associated with creating a general methodology for multi sensor integration and fusion-focusing on the methods used for modeling error or uncertainty in the integration and fusion process (e.g., the registration problem), the actual sensory information (i.e., the sensor model), and the operation of the overall system (e.g., multi sensor calibration). © 1989 IEEENavigation--Inertial Systems; Radar--Tracking; Remote Sensing; Robotics; Sensors; Decision Tree; Fuzzy Logic; Military Command/Control; Multisensor Fusion Methods; Multisensor Integration; Target Tracking; Artificial Intelligencejournal article10.1109/21.44007https://www.scopus.com/inward/record.uri?eid=2-s2.0-0024737615&doi=10.1109%2f21.44007&partnerID=40&md5=6aa0fb899ec7a4eebcb1d0a7dc080330https://doi.org/10.1109/21.44007