Information Fusion and Decision Support for Autonomous Systems

In this talk we present our works on decision support analytic for autonomous systems. Decision support analytic process multiple sensory information collected by an autonomous system such as lidar, camera, RGBD, acoustic to perform signal detection, target tracking, object recognition. As multiple sensors are involved, our system uses sensor registration, data association and fusion to combine sensory information. The next layer of the proposed decision support system orients the processed sensory information at feature and classification levels to perform situation assessment and treat evaluation. Based on the assessment, the decision support system will recommend decision. If the uncertainty is high, actions including resource allocation, planning will be used to extract or reassess the sensory information to get a recommended decision with lower uncertainty. This talk will also presents the applications of the proposed decision support analytic in four industrial projects including 1) goal-driven net-enabled distributed sensing for maritime surveillance, 2) autonomous navigation and perception of humanoid service robots, 3) distance learning for oil and gas drilling and 4) cognitive vehicles.

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