Guaranteed set-membership state estimation of an octorotor's position for radar applications

Abstract

In the context of state estimation of dynamical systems subject to bounded perturbations and measurement noises, this paper proposes an application of a guaranteed ellipsoidal-based set-membership state estimation technique to estimate the linear position of an octorotor used for radar applications. The size of the ellipsoidal set containing the real state is minimized at each sample time taking into account the measurements performed by the drone's sensors. Three case studies highlight the efficiency of the estimation technique in finding guaranteed bounds for the octorotor's linear position. The computed guaranteed bounds in the linear trajectory are exploited to find the maximum operating frequency of the radar, a necessary information in radar applications.

Set‐theoretic localization for mobile robots with infrastructure‐based sensing

“…Our method has a similar structure as the convectional filtering algorithms that predict the states via a dynamics model and subsequently update the prediction using sensor measurements. Unlike the probabilistic methods such as the EKF, the proposed algorithm uses set‐valued motion prediction and measurement update to yield a deterministic estimation of uncertainty bounds for robotics localization, mapping, and system state estimation problems 7,14‐19 …”

“…Unlike the probabilistic methods such as the EKF, the proposed algorithm uses set-valued motion prediction and measurement update to yield a deterministic estimation of uncertainty bounds for robotics localization, mapping, and system state estimation problems. 7,[14][15][16][17][18][19] In scenarios of real-time exploration tasks, SLAM algorithms are necessary as the environment information is unknown to the robots. 1 For SLAM problems, probabilistic methods, for example, EKF SLAM 20,21 and FastSLAM 5 have been developed and widely adopted.…”

Set-theoretic Localization for Mobile Robots with Infrastructure-based Sensing

“…In contrast to the above probabilistic and optimization methods, set-theoretic methods enable a deterministic estimation of uncertainty bounds for robotics localization, mapping and system state estimation problems [27], [28], [29], [6], [30], [31], [32]. Inspired by [6], we propose a set-theoretic localization algorithm which use infrastructure-based sensors for mobile robots localization.…”

Zonotopic Kalman Filter-Based Interval Estimation for Discrete-Time Linear Systems With Unknown Inputs

“…main difficulty of designing interval observers is to find a change of coordinates for the system to satisfy the so-called cooperativity property [7] since this change of coordinates greatly influences the accuracy of the observer. This difficulty can be circumvented by using SME strategies which consist in finding geometrical sets, such as ellipsoids [14], zonotopes [11], [12], [15] or polytopes [16], to approximate the FSS. While polytopic sets provide a good estimation accuracy, methods using them are computationally expensive.…”