Title :
Minimum-energy state estimation for systems with perspective outputs and state constraints
Author :
Aguiar, António Pedro ; Hespanha, Joao P.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
Abstract :
We address the problem of estimating the state of a system with perspective outputs, whose state is known to satisfy a set of quadratic constraints. We construct a dynamical system that produces an estimate of the state that satis#es the constraints and is "most compatible" with the dynamics, in the sense that it requires the least amount of noise energy to explain the measured output. We apply these results to the estimation of position and orientation of a controlled rigid body, using measurements from a charged-coupled-device (CCD) camera attached to the body. The main contribution of this work is the inclusion of state constraints in the minimum-energy formulation. In the context of our application, these constraints allow us to avoid singularities that previous minimum-energy controllers encountered. The results are validated experimentally by using measurements from a CCD camera mounted on a mobile robot to estimate its position and orientation. These estimates are then used to close the loop and control the robot to a desired position, de#ned with respect to visual landmarks. The use of state constraints in the estimator allow the system to operate even when the trajectories for the robot do not exhibit "excitation," which was needed in previous minimum-energy estimators.
Keywords :
CCD image sensors; constraint theory; mobile robots; position control; state estimation; CCD camera; charged coupled device camera; dynamical system; minimum energy controllers; minimum energy state estimation; mobile robot; noise energy; orientation estimation; perspective outputs; position estimation; quadratic constraints; state constraints; visual landmarks; Cameras; Charge coupled devices; Charge-coupled image sensors; Current measurement; Energy measurement; Mobile robots; Noise measurement; Position measurement; Robot vision systems; State estimation;
Conference_Titel :
Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
Print_ISBN :
0-7803-7924-1
DOI :
10.1109/CDC.2003.1272395