UWB-based Multiple UAV Control System for Indoor Ground Vehicle Tracking

Lee, Joohyun; Moon, Jiseon; Kim, Sunwoo

doi:10.1109/apwcs50173.2021.9548721

Cited by 10 publications

(3 citation statements)

References 10 publications

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“…An overview of this concept can be found in [8]. However, these systems, which are within an affordable range, achieve an accuracy of about 10 cm, as shown by the example of UWB [9]. If one imagines that the dimensions of the MU are of this order of magnitude, it becomes clear that the level of accuracy required for a robotic arm to correctly grip the MU without damaging it is too low.…”

Section: Robotic Armmentioning

confidence: 99%

Object Localization by Construction of an Asymmetric Isobody of the Magnetic Gradient Tensor Contraction Using Two Identical Permanent Magnets

et al. 2023

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This paper deals with predictive maintenance of infrastructure objects, focusing on the inspection of bridges. To achieve this goal, unmanned aerial vehicles place measuring units for data collection at different points of the bridge. This work deals with the question of how these measuring units can be found and removed by them later. For this purpose, a magnetic localization method based on the STAR method is presented. In contrast to the STAR method, which only detects the center of a magnetic target, a modified version called SRIOD is implemented here, where the orientation of the magnetic target can also be detected. This is essential information if the unmanned aerial vehicle is to grab the measuring unit with a robotic arm. In this regard, two identical permanent magnets are integrated into the measuring unit, whose gradient tensor contraction of the magnetic flux density distribution has a directed asymmetric surface when considering the contours of constant values. This creates a magnetic invisible reference plane that can be detected with a magnetic gradiometer. The method is verified both in simulation and experimentally in a laboratory setup.

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Section: Robotic Armmentioning

confidence: 99%

Object Localization by Construction of an Asymmetric Isobody of the Magnetic Gradient Tensor Contraction Using Two Identical Permanent Magnets

et al. 2023

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“…In outdoor environments, where geostationary satellites are in LOS (line-of-sight) condition, the GPS signal is used to obtain information about position and velocity of a mobile object (see, for example, [4][5][6][7][8][9]), together with a data fusion system [10] which is able to handle the different nature and frequency of IMU measures and GPS signals. In other contexts, where the GPS signal becomes unreliable, for example, in indoor environments [11,12] or outdoor scenarios such as forests or urban canyons [13], it is necessary to use alternative sensor devices and methods to face the localization problem [14][15][16][17]. A common way to approach this kind of problem is to perform the navigation task in a structured environment where it is possible to take information about the distance between the moving object and some fixed reference points.…”

Section: Introductionmentioning

confidence: 99%

Localization in Structured Environments with UWB Devices without Acceleration Measurements, and Velocity Estimation Using a Kalman–Bucy Filter

Alonge

Cusumano

D’Ippolito

et al. 2022

Sensors

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In this work, a novel scheme for velocity and position estimation in a UWB range-based localization system is proposed. The suggested estimation strategy allows to overcome two main problems typically encountered in the localization systems. The first one is that it can be suitable for use in environments where the GPS signal is not present or where it might fail. The second one is that no accelerometer measurements are needed for the localization task. Moreover, to deal with the velocity estimation problem, a suitable Kalman–Bucy filter is designed and it is compared, experimentally, with a particle filter by showing the features of the two algorithms in order to be used in a localization context. Additionally, further experimental tests are carried out on a suitable developed test setup in order to confirm the goodness of the proposed approach.

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“…Despite these challenging aspects, recent IoT-inspired technological trends boost the employment of autonomous aerial vehicles to perform different tasks in indoor scenarios, especially in the emerging smart domestic and industrial contexts. These include, for instance, cooperative monitoring [ 13 ], ground robots tracking [ 14 ], infrastructures contact inspection [ 15 ], people and objects detection [ 16 ], items transportation [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Indoor Visual-Based Localization System for Multi-Rotor UAVs

Bertoni

Michieletto

Oboe

et al. 2022

Sensors

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Industry 4.0, smart homes, and the Internet of Things are boosting the employment of autonomous aerial vehicles in indoor environments, where localization is still challenging, especially in the case of close and cluttered areas. In this paper, we propose a Visual Inertial Odometry localization method based on fiducial markers. Our approach enables multi-rotor aerial vehicle navigation in indoor environments and tackles the most challenging aspects of image-based indoor localization. In particular, we focus on a proper and continuous pose estimation, working from take-off to landing, at several different flying altitudes. With this aim, we designed a map of fiducial markers that produces results that are both dense and heterogeneous. Narrowly placed tags lead to minimal information loss during rapid aerial movements while four different classes of marker size provide consistency when the camera zooms in or out according to the vehicle distance from the ground. We have validated our approach by comparing the output of the localization algorithm with the ground-truth information collected through an optoelectronic motion capture system, using two different platforms in different flying conditions. The results show that error mean and standard deviation can remain constantly lower than 0,11m, so not degrading when the aerial vehicle increases its altitude and, therefore, strongly improving similar state-of-the-art solutions.

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UWB-based Multiple UAV Control System for Indoor Ground Vehicle Tracking

Cited by 10 publications

References 10 publications

Object Localization by Construction of an Asymmetric Isobody of the Magnetic Gradient Tensor Contraction Using Two Identical Permanent Magnets

Object Localization by Construction of an Asymmetric Isobody of the Magnetic Gradient Tensor Contraction Using Two Identical Permanent Magnets

Localization in Structured Environments with UWB Devices without Acceleration Measurements, and Velocity Estimation Using a Kalman–Bucy Filter

Indoor Visual-Based Localization System for Multi-Rotor UAVs

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