Online Optimal Perception-Aware Trajectory Generation - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Robotics Année : 2019

Online Optimal Perception-Aware Trajectory Generation

Résumé

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 andwe 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.
Fichier principal
Vignette du fichier
TRO2019_FinalVersion.pdf (4.5 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-02278900 , version 1 (04-09-2019)

Identifiants

Citer

Paolo Salaris, Marco Cognetti, Riccardo Spica, Paolo Robuffo Giordano. Online Optimal Perception-Aware Trajectory Generation. IEEE Transactions on Robotics, 2019, pp.1-16. ⟨10.1109/TRO.2019.2931137⟩. ⟨hal-02278900⟩
104 Consultations
463 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More