Multi-step sensor selection with position uncertainty constraints

摘要: Research on localization systems has shifted from focusing mainly accuracy towards a more cognitive design, accounting for communication constraints, energy limitations, and delay. This leads to variety of sensor selection optimization problems that are solved using techniques convex optimization. We provide novel formulation the problem over an extended time horizon, aiming minimize sensing cost entire path while guaranteeing certain position accuracy. state algorithms determining lower upper bounds utilize these in autonomous agents. Simulation results confirm usefulness our approach, where we observe benefit optimizing longer horizons low medium noise scenarios compared myopic scheme.