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    Online Optimal Perception-Aware Trajectory Generation


    Salaris, Paolo and Cognetti, Marco and Spica, Riccardo and Giordano, Paolo Robuffo (2019) Online Optimal Perception-Aware Trajectory Generation. IEEE Transactions on Robotics, 35 (6). pp. 1307-1322. ISSN 1552-3098

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    Abstract

    This article 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. In this article, 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.

    Item Type: Article
    Keywords: Active estimation; calibration; identification; localization; reactive trajectory planning;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15322
    Identification Number: https://doi.org/10.1109/TRO.2019.2931137
    Depositing User: Marco Cognetti
    Date Deposited: 24 Jan 2022 15:27
    Journal or Publication Title: IEEE Transactions on Robotics
    Publisher: IEEE
    Refereed: Yes
    URI:

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