Statistical modeling and design issues of a crossbeam sensor

The basic idea of RISC (reduced intricacy sensing and control) robotics is an attempt to perform challenging industrial manufacturing tasks by using a combination of simple hardware and sophisticated algorithms. Many effective strategies and algorithms have been explored. However, the issue of optimal design of RISC sensor has not been solved. The main reason is the shortage of good models. In this paper, we propose a statistical model for one of the typical RISC sensors, i.e. the crossbeam sensor. Based on this statistical model we employ the multiple hypotheses-testing method as optimal design technique and present its applied strategies. It is believed that this work will lead to development of new RISC sensors because a new principle and a pertinent model are introduced into this area.