Globally convergent visual-feature range estimation with biased inertial measurements

Jin, Chi; Manchester, Ian R.

doi:10.1016/j.automatica.2022.110639

Cited by 3 publications

(6 citation statements)

References 23 publications

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“…with t ′ c := t 0 +t c , in which we have used the non-negativeness property ∆ i (t) ≥ 0, ∀t ≥ 0 and the Cauchy-Schwarz inequality for integrals. For the LTV system (37), it is well known that the global exponential stability (GES) is equivalent to ∆ e i being PE, which has been verified in (39). Therefore, the error dynamics admits the exponential convergence (30) under the IE condition of ϕ i .…”

Section: A Mapping Observer In the Dynamic Extension Framementioning

confidence: 93%

“…An alternative to generate a linear regressor may be found in [21] by augmenting both the position v ℓ i and its range | v ℓ i | in the systems state. Recently, a new linear parameterization to the feature range in the bodyfixed frame {B} is proposed in [37] using linear stable filters.…”

Section: B a Linear Least Squares Solutionmentioning

confidence: 99%

“…The second claim is verified invoking ∆ e i are scalar signals. Recalling the dynamics of v li in (37), the last claim is equivalent to verify ∆ e i ∈ PE. To simplify the presentation, we neglect the index i of the IE condition from the i-th feature points.…”

Section: A Mapping Observer In the Dynamic Extension Framementioning

confidence: 99%

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An almost globally convergent observer for visual SLAM without persistent excitation

Jin

Wang

Shi

et al. 2021

2021 60th IEEE Conference on Decision and Control (CDC)

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This paper introduces a new linear parameterization to the problem of visual inertial simultaneous localization and mapping (VI-SLAM)-without anyapproximation-for the case only using information from a single monocular camera and an inertial measurement unit. In this problem set, the system state evolves on the nonlinear manifold SE(3)×R 3n , on which we design dynamic extensions carefully to generate invariant foliations, such that the problem can be reformulated into online constant parameter identification, then interestingly with linear regression models obtained. It demonstrates that VI-SLAM can be translated into a linear least squares problem, in the deterministic sense, globally and exactly. Based on this observation, we propose a novel SLAM observer, following the recently established parameter estimation-based observer (PEBO) methodology. A notable merit is that the proposed observer enjoys almost global asymptotic stability, requiring neither persistency of excitation nor uniform complete observability, which, however, are widely adopted in most existing works with provable stability but can hardly be assured in many practical scenarios.

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Section: A Mapping Observer In the Dynamic Extension Framementioning

confidence: 93%

Section: B a Linear Least Squares Solutionmentioning

confidence: 99%

See 1 more Smart Citation

An almost globally convergent observer for visual SLAM without persistent excitation

Jin

Wang

Shi

et al. 2021

2021 60th IEEE Conference on Decision and Control (CDC)

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show abstract

“…In this section, we present a distributed finite‐time sliding mode observer for range estimation among spatial vehicles based on the relative bearing, attitude, and local velocity measurements in the formation. Observer design for the range estimation problem between a spatial robot and a static feature point is presented in References 40,41. Compared to the observers presented in Reference 41, the sliding mode observer proposed in this work can be applied to moving objects, avoids open‐loop integration, and guarantees finite‐time estimation.…”

Section: Range Observer Designmentioning

confidence: 99%

“…Observer design for the range estimation problem between a spatial robot and a static feature point is presented in References 40,41. Compared to the observers presented in Reference 41, the sliding mode observer proposed in this work can be applied to moving objects, avoids open‐loop integration, and guarantees finite‐time estimation.…”

Section: Range Observer Designmentioning

confidence: 99%

Range observer‐based formation control for heterogeneous spatial underactuated vehicle networks

Wang

Nersesov

Ashrafiuon

2023

Adaptive Control & Signal

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In this work, we solve the distributed formation control problem for heterogeneous spatial underactuated vehicle networks subject to switching topologies.We consider the spatial rigid body model of underwater and aerial vehicles with one translational actuator for propulsion and three rotational actuators, without any simplification. A distributed finite-time sliding mode observer is designed to estimate the ranges between vehicles based on the bearing angles, and thus, the control design does not require relative position or distance measurements.A coordinate transformation is proposed to define continuous reference velocity trajectories under switching topologies. Then, based on the cascade structure, a distributed formation protocol is presented which guarantees the global asymptotic convergence for the closed-loop system. The formation controller has a simple structure, requires only neighbor-to-neighbor information exchange, and all the measurements may be obtained using simple onboard sensors. Numerical simulations for a group of heterogeneous spatial underactuated vehicles including autonomous underwater vehicles and quadrotors are presented.

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Attitude Estimation From Vector Measurements: Necessary and Sufficient Conditions and Convergent Observer Design

Wang

Manchester

2024

IEEE Trans. Automat. Contr.

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Globally convergent visual-feature range estimation with biased inertial measurements

Cited by 3 publications

References 23 publications

An almost globally convergent observer for visual SLAM without persistent excitation

An almost globally convergent observer for visual SLAM without persistent excitation

Range observer‐based formation control for heterogeneous spatial underactuated vehicle networks

Attitude Estimation From Vector Measurements: Necessary and Sufficient Conditions and Convergent Observer Design

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