6,352 research outputs found
Least-square based recursive optimization for distance-based source localization
In this paper we study the problem of driving an agent to an unknown source
whose location is estimated in real-time by a recursive optimization algorithm.
The optimization criterion is subject to a least-square cost function
constructed from the distance measurements to the target combined with the
agent's self-odometry. In this work, two important issues concerning real world
application are directly addressed, which is a discrete-time recursive
algorithm for concurrent control and estimation, and consideration for input
saturation. It is proven that with proper choices of the system's parameters,
stability of all system states, including on-board estimator variables and the
agent-target relative position can be achieved. The convergence of the agent's
position to the target is also investigated via numerical simulation
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