Simulation-based sensing-system configuration for dynamic dispatching

The paper presents a methodology for determining the initial configuration of a set of sensors for a surveillance task. It serves to complement a dynamic dispatching methodology, which selects and maneuvers subsets of sensors to achieve optimal data acquisition in real-time. Specifically, given a priori information about the expected object trajectory, the initial sensor poses are determined such that the sensing-system effectiveness is maximized. This is achieved using a constrained, nonlinear, direct search method in combination with simulations of the sensing-system performance (i.e., dynamic dispatching to adjust the sensor poses in response to the object motion).

[1]  Takashi Matsuyama,et al.  Active Image Capturing and Dynamic Scene Visualization by Cooperative Distributed Vision , 1998, AMCP.

[2]  David Mautner Himmelblau,et al.  Applied Nonlinear Programming , 1972 .

[3]  Ren C. Luo,et al.  Multisensor integration and fusion for intelligent machines and systems , 1995 .

[4]  Beno Benhabib,et al.  Dispatching of Coordinated Proximity Sensors for Object Surveillance , 2001, Dynamic Systems and Control.

[5]  Andrew M. Wallace,et al.  Model-based planning of optimal sensor placements for inspection , 1997, IEEE Trans. Robotics Autom..

[6]  Hong Zhang Two-dimensional optimal sensor placement , 1995, IEEE Trans. Syst. Man Cybern..

[7]  Beno Benhabib,et al.  Dynamic dispatching of coordinated sensors , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.

[8]  David M. Himmelblau,et al.  Constrained Nonlinear Optimization by Heuristic Programming , 1969, Oper. Res..