Sensor planning with hierarchically distributed perception net

A new paradigm of sensor planning is presented based on a hierarchically distributed perception net (HDPN) proposed as a general sensing architecture. The sensor planning is done by optimizing the parameters as well as the structures of HDPN for the given sensing goals denoted respectively as parametric and structural sensor planning. In the proposed parametric sensor planning, the sensing parameters of HDPN are iteratively modified so that HDPN ultimately generates the desired accuracy of outputs at a minimum sensing cost. The structural sensor planning aims at self-organizing an optimal configuration of HDPN by exploiting redundant sensing. A simulation study is conducted by applying the proposed parametric sensor planning method for the accurate self-localization of a mobile robot operating in a known environment with multiple range sensors. Simulation results verify the validity of the proposed method. The proposed paradigm provides a formal, yet general and efficient method of representing and solving a sensor planning problem for an integrated sensor system