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On Multi-Step Sensor Scheduling via Convex Optimization

Konferenzbeitrag

Links:
Autor:

Marco F. Huber

Quelle:

Proceedings of the 2nd International Workshop on Cognitive Information Processing (CIP), 2010.

Seiten:

376-381

Konferenz:

2nd International Workshop on Cognitive Information Processing (CIP), Elba Island, Italy, 14.-16. Juni 2010

Effective sensor scheduling requires the consideration of long-term effects and thus optimization over long time horizons. Determining the optimal sensor schedule, however, is equivalent to solving a binary integer program, which is computationally demanding for long time horizons and many sensors. For linear Gaussian systems, two efficient multi-step sensor scheduling approaches are proposed in this paper. The first approach determines approximate but close to optimal sensor schedules via convex optimization. The second approach combines convex optimization with a branch-and-bound search for efficiently determining the optimal sensor schedule.