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Many potential accidents due to direct control of electrical wheelchair may be occurred by unreasonable control in various internal or external environmental conditions, such as the uncertainties of the front caster wheels and the unbalanced friction condition between wheels and floor. This paper presents a Grey-Fuzzy Decision-Making (GFD) algorithm based on grey prediction theory and fuzzy logic theory. The GFD is able to estimate optimal parameters approximating to the real system dynamics mode according to the observed information. The application of intelligent assistant control of an electrical wheelchair is investigated. We conduct the experiments by multisensor based wheelchairs "Luoson#l " and "Luoson#3". The GFD controller is presented to integrate the electronic compass and dead reckoning measurements for the reduction of the influence caused by the uncertainties. The results have demonstrated the system capability for the increased certainty and safety to operate the electrical wheelchairs.

The objective of this paper is to describe the development of a distributed MultiAgent Sensory Information Fusion system which integrates data from multiple sensors such as laser radac weather radar, forward looking infrared sensors (FLIR) and associated important sensory information located in diflerent agents to accomplish requested tasks cooperatively. In this paper, we have developed a system based on the concept of ODoard Augmented Theater Surveillance (OBATS) and Internet network architecture to make the multi-agent resource management system in practice. The architecture of distributed fusion system, the coordination strategy of Global Decision Agent (GDA) and the communication between Service Agents (SAS) and GDA have been developed. Furthermore, a scenario application has been implemented to demonstrate the concept of this multi-agent system. Other potential applications have also been discussed.

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