Observability Analysis for AUV Range-only Localization and Mapping Measures of Unobservability and Experimental Results

2012 ◽  
Vol 45 (27) ◽  
pp. 325-330 ◽  
Author(s):  
Mohammadreza Bayat ◽  
A. Pedro Aguiar
Author(s):  
Mohammadreza Bayat ◽  
A. Pedro Aguiar

Purpose – The authors aim to investigate the observability properties of the process of simultaneous localization and mapping of an autonomous underwater vehicle (AUV), a challenging and important problem in marine robotics, and illustrate the derived results through computer simulations and experimental results with a real AUV. Design/methodology/approach – The authors address the single/multiple beacon observability analysis of the process of simultaneous localization and mapping of an AUV by deriving the nonlinear mathematical model that describes the process; then applying a suitable coordinate transformation, and subsequently a time-scaling transformation to obtain a linear time varying (LTV) system. The AUV considered is equipped with a set of inertial sensors, a depth sensor, and an acoustic ranging device that provides relative range measurements to a set of stationary beacons. The location of the beacons does not need to be necessarily known and in that case, the authors are also interested to localize them. Numerical tests and experimental results illustrate the derived theoretical results. Findings – The authors show that if either the position of one of the beacons or the initial position of the AUV is known, then the system is at least locally weakly observable, in the sense that the set of indistinguishable states from a given initial configuration contains a finite set of isolated points. The simulations and experiments results illustrate the findings. Originality/value – In the single and multiple beacon case and for manoeuvres with constant linear and angular velocities both expressed in the body-frame, known as trimming or steady-state trajectories, the authors derive conditions under which it is possible to infer the state of the resulting system (and in particular the position of the AUV). The authors also describe the implementation of an advanced continuous time constrained minimum energy observer combined with multiple model techniques. Numerical tests and experimental results illustrate the derived theoretical results.


Robotica ◽  
2010 ◽  
Vol 29 (6) ◽  
pp. 805-814 ◽  
Author(s):  
Farhad Aghili

SUMMARYThis paper investigates 3-dimensional (3D) Simultaneous Localization and Mapping (SLAM) and the corresponding observability analysis by fusing data from landmark sensors and a strap-down Inertial Measurement Unit (IMU) in an adaptive Kalman filter (KF). In addition to the vehicle's states and landmark positions, the self-tuning filter estimates the IMU calibration parameters as well as the covariance of the measurement noise. The discrete-time covariance matrix of the process noise, the state transition matrix and the observation sensitivity matrix are derived in closed form, making it suitable for real-time implementation. Examination of the observability of the 3D SLAM system leads to the the conclusion that the system remains observable, provided that at least three known landmarks, which are not placed in a straight line, are observed.


Author(s):  
Marco A. Arteaga-Pérez ◽  
Alejandro Gutiérrez-Giles ◽  
Jens Weist

In this paper, an observability analysis for differential pneumatic pistons is presented, together with the design and implementation of linear observers of the Luenberger type. To avoid as much as possible the knowledge of the system model parameters, the generalized proportional integral (GPI) approach is employed for the estimation of unmeasured variables. Experimental results show the good performance of the proposed scheme.


Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3063
Author(s):  
Jun Cheng ◽  
Liyan Zhang ◽  
Qihong Chen

In the aim of improving the positioning accuracy of the monocular visual-inertial simultaneous localization and mapping (VI-SLAM) system, an improved initialization method with faster convergence is proposed. This approach is classified into three parts: Firstly, in the initial stage, the pure vision measurement model of ORB-SLAM is employed to make all the variables visible. Secondly, the frequency of the IMU and camera was aligned by IMU pre-integration technology. Thirdly, an improved iterative method is put forward for estimating the initial parameters of IMU faster. The estimation of IMU initial parameters is divided into several simpler sub-problems, containing direction refinement gravity estimation, gyroscope deviation estimation, accelerometer bias, and scale estimation. The experimental results on the self-built robot platform show that our method can up-regulate the initialization convergence speed, simultaneously improve the positioning accuracy of the entire VI-SLAM system.


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