No abstract

In this paper, we illustrate the application of a nonlinear active structure estimation from motion (SfM) strategy to three problems, namely, 3D structure estimation for (i) a point, (ii) a sphere and, (iii) a cylinder. In all three cases, an appropriate parametrization reduces the problem to the estimation of a single quantity. Knowledge of this estimated quantity and of the available measurements allows for then retrieving the full 3D structure of the observed objects. Furthermore, in the point feature case, two different parametrizations based on either a planar or a spherical projection model are critically compared: indeed, the two models yield, somehow unexpectedly, to different convergence properties for the SfM estimation task. The reported simulative and experimental results fully support the theoretical analysis and clearly show the benefits of the proposed active estimation strategy, which is in particular able to impose a desired transient response to the estimation error equivalent to that of a reference linear second-order system with assigned poles.

This paper proposes an online optimal active perception strategy for differentially flat systems meant to maximize the information collected via the available measurements along the planned trajectory. The goal is to generate online a trajectory that minimizes the maximum state estimation uncertainty provided by the employed observer. To quantify the richness of the acquired information about the current state, the smallest eigenvalue of the Constructibility Gramian is adopted as a metric. We use B-Splines for parametrizing the trajectory of the flat outputs and we exploit a constrained gradient descent strategy for optimizing online the location of the B-Spline control points in order to actively maximize the information gathered over the whole planning horizon. To show the effectiveness of our method in maximizing the estimation accuracy, we consider two case studies involving a unicycle and a quadrotor that need to estimate their poses while measuring two distances w.r.t. two fixed landmarks. Concurrent estimation of calibration/environment parameters is also considered for illustrating how the proposed method copes with instances of active self-calibration and map building.