  In this work, we present a framework that enables a vehicle to autonomously
localize a target based on noisy range measurements computed from RSSI data. To
achieve the mission objectives, we develop a control scheme composed of two
main parts: an estimator and a motion planner. At each time step, new estimates
of the target's position are computed and used to generate and update
distribution functions using Bernstein polynomials. A metric of the efficiency
of the estimator is derived based on the Fisher Information Matrix. Finally,
the motion planning problem is formulated to react in real time to new
information about the target and improve the estimator's performance.

Systems and Control;Robotics;Systems and Control