Multilayer sensing and aggregation approach to environmental perception with one multifunctional sensor

This paper presents a novel approach to perception of a specified environment for intelligent system or robotics applications in which high-level information must be extracted from multi-sensors data. A CdS and Fe₃O₄ material based multifunction sensor has been developed to measure temperature, humidity and brightness. The sensor focuses on the processing of the multifunctional information in a multilayer framework, which is more attractive in terms of system simplicity, performance, and compact structure. Further along, quantity creditability tactics (QCT), one multisensing data fusion method, is approached, with which quantities are sequentially aggregated to generate a general perception about the sensed environment. Different from the popular fusion strategies, the proposed algorithm also works in a step-by-step framework, and proves to be more practical and more effective when there are more variables for calculation