Journal
APPLIED ARTIFICIAL INTELLIGENCE
Volume 27, Issue 3, Pages 235-248Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/08839514.2013.769078
Keywords
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Funding
- National Natural Science Foundation of China [61174022]
- Chongqing Natural Science Foundation (CSCT) [2010BA2003]
- National High Technology Research and Development Program of China (863 program) [2013AA013801]
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In multisensor systems, complementary observations from different sensors need to be combined with each other. Due to the uncertainty, sensor reports can be represented by fuzzy sets in order to efficiently deal with signal processing. In this article, a methodology to combine sensor reports in fuzzy environments based on DempsterShafer evidence theory is proposed. The basic probability assignment function is constructed by means of member functions. The numerical example on object recognition of a robot arm is shown to illustrate the efficiency of the presented approach.
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