Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Review Article Machine Perception in Automation: A Call to Arms | Hindawi Publishing Corporation EURASIP Journal on Embedded Systems Volume 2011 Article ID 608423 9 pages doi 2011 608423 Review Article Machine Perception in Automation A Call to Arms Dietmar Bruckner 1 Rosemarie Velik 1 2 and Yoseba Penya3 1 Institute of Computer Technology Vienna University of Technology 1040 Vienna Austria 2 Fatronik-Tecnalia Biorobotics 20009 Donostia-San Sebastian Spain 3 University ofDeusto 20012 Donostia Basque Country Spain Correspondence should be addressed to Dietmar Bruckner bruckner@ Received 28 June 2010 Revised 5 November 2010 Accepted 16 January 2011 Academic Editor Klaus Kabitzsch Copyright 2011 Dietmar Bruckner et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Automation systems strongly depend on the amount quality and richness of their sensor information. For decades scientists have investigated towards more accurate and cheaper sensors as well as new sensors for previously undetectable properties or substances. With these enhancements the problem of too complex sensor information and sensor fusion raised. This paper is intended for giving a retrospection on perception systems in automation followed by reviewing state-of-the-art approaches for handling diverse and complex sensor information as well as highlighting future requirements for more human-like systems that have the ability of performing their actions in complex and unpredictable environments. For the latter requirement a section introducing a number of agent architectures for embedding the sensor fusion process into a comprehensive decision-making unit is given. 1. Introduction The imaginary accumulated by science fiction through the years has always fancied future worlds full of intelligent autonomous machines that were able to perceive the reality around. This ability of sensing
