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An almost globally convergent observer for visual SLAM without persistent excitation

2021/04/07 by Bowen Yi, Chi Jin, Yi, Bowen +7
Computer Science · Engineering · #Advanced Vision and Imaging #FOS: Computer and information sciences #FOS: Electrical engineering #Robotics (cs.RO) #Robotics and Sensor-Based Localization #Sparse and Compressive Sensing Techniques #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2104.02966

openalex publication_date 2021/04/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In this paper we propose a novel observer to solve the problem of visual simultaneous localization and mapping (SLAM), only using the information from a single monocular camera and an inertial measurement unit (IMU). The system state evolves on the manifold SE(3)× ℝ3n, on which we design dynamic extensions carefully in order to generate an invariant foliation, such that the problem is reformulated into online constant parameter identification. Then, following the recently introduced parameter estimation-based observer (PEBO) and the dynamic regressor extension and mixing (DREM) procedure, we provide a new simple solution. A notable merit is that the proposed observer guarantees almost global asymptotic stability requiring neither persistency of excitation nor uniform complete observability, which, however, are widely adopted in most existing works with guaranteed stability.

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