Multi-UAV formation geometries for cooperative navigation in GNSS-challenging environments

Causa, Flavia; Vetrella, Amedeo Rodi; Fasano, Giancarmine; Accardo, Domenico

doi:10.1109/plans.2018.8373453

Cited by 51 publications

(31 citation statements)

References 13 publications

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“…A feasibility study and the implications of such scheme on the accuracy of the reconstructed 3D models from D2 imagery were discussed in the work by the authors of [18], whereas the first prototype was presented in the work by the authors of [19]. A similar concept has been explored in [20], where multiple "father" UAVs help to localize a "son" UAV, fusing opportunistic GNSS observations with collaborative measurements. With respect to this work, we present and evaluate a real-world implementation of a visual ranging algorithm that allows to reduce the requirements to only one "father" UAV.…”

Section: Background and Motivationsmentioning

confidence: 99%

Photometric Long-Range Positioning of LED Targets for Cooperative Navigation in UAVs

Jospin

Stoven-Dubois

Cucci

2019

Drones

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Autonomous flight with unmanned aerial vehicles (UAVs) nowadays depends on the availability and reliability of Global Navigation Satellites Systems (GNSS). In cluttered outdoor scenarios, such as narrow gorges, or near tall artificial structures, such as bridges or dams, reduced sky visibility and multipath effects compromise the quality and the trustworthiness of the GNSS position fixes, making autonomous, or even manual, flight difficult and dangerous. To overcome this problem, cooperative navigation has been proposed: a second UAV flies away from any occluding objects and in line of sight from the first and provides the latter with positioning information, removing the need for full and reliable GNSS coverage in the area of interest. In this work we use high-power light-emitting diodes (LEDs) to signalize the second drone and we present a computer vision pipeline that allows to track the second drone in real-time from a distance up to 100 m and to compute its relative position with decimeter accuracy. This is based on an extension to the classical iterative algorithm for the Perspective-n-Points problem in which the photometric error is minimized according to a image formation model. This extension allow to substantially increase the accuracy of point-feature measurements in image space (up to 0.05 pixels), which directly translates into higher positioning accuracy with respect to conventional methods.

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Section: Background and Motivationsmentioning

confidence: 99%

Photometric Long-Range Positioning of LED Targets for Cooperative Navigation in UAVs

Jospin

Stoven-Dubois

Cucci

2019

Drones

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“…The approach proposed in this paper is conceived to be integrated within two navigation architectures capable of enabling: high-accuracy attitude estimation for UAVs flying under nominal GNSS coverage [ 17 ]; safe autonomous navigation for UAVs flying in GNSS-challenging environments [ 35 ]. …”

Section: Cooperative Multi-uav Applicationsmentioning

confidence: 99%

“…In [ 35 ], the authors presented the concept of enabling safe autonomous navigation of a UAV (son) flying in GNSS-challenging environments (e.g., natural/urban canyons where the GNSS position fix may not be enabled, or reliable, due to the lack of enough measurement) by exploiting cooperation with another UAV (father) flying under nominal GNSS coverage. Specifically, the absolute position of the father (provided through an inter-vehicle data-link), the son-father LOS (provided by the target visual detection and tracking block) and additional pseudo-ranges (if available at the GNSS receiver of the son) are combined within an original sensor fusion scheme based on an Extended Kalman Filter (EKF).…”

Section: Cooperative Multi-uav Applicationsmentioning

confidence: 99%

A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications

Opromolla

Fasano

Accardo

2018

Sensors

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This paper presents a visual-based approach that allows an Unmanned Aerial Vehicle (UAV) to detect and track a cooperative flying vehicle autonomously using a monocular camera. The algorithms are based on template matching and morphological filtering, thus being able to operate within a wide range of relative distances (i.e., from a few meters up to several tens of meters), while ensuring robustness against variations of illumination conditions, target scale and background. Furthermore, the image processing chain takes full advantage of navigation hints (i.e., relative positioning and own-ship attitude estimates) to improve the computational efficiency and optimize the trade-off between correct detections, false alarms and missed detections. Clearly, the required exchange of information is enabled by the cooperative nature of the formation through a reliable inter-vehicle data-link. Performance assessment is carried out by exploiting flight data collected during an ad hoc experimental campaign. The proposed approach is a key building block of cooperative architectures designed to improve UAV navigation performance either under nominal GNSS coverage or in GNSS-challenging environments.

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“…In the modern world, people are becoming increasingly dependent on location services. The need to provide accurate indoor location services is becoming more and more urgent [1][2][3][4][5]. Indoor positioning technologies based on various types of sensors, such as Wi-Fi [6], Bluetooth [7], cameras [8], and inertial sensors [9], are rapidly developing.…”

Section: Introductionmentioning

confidence: 99%

Pedestrian Dead Reckoning-Assisted Visual Inertial Odometry Integrity Monitoring

Peng

Lin

et al. 2019

Sensors

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Visual inertial odometers (VIOs) have received increasing attention in the area of indoor positioning due to the universality and convenience of the camera. However, the visual observation of VIO is more susceptible to the environment, and the error of observation affects the final positioning accuracy. To address this issue, we analyzed the causes of visual observation error that occur under different scenarios and their impact on positioning accuracy. We propose a new method of using the short-time reliability of pedestrian dead reckoning (PDR) to aid in visual integrity monitoring and to reduce positioning error. The proposed method selects optimized positioning by automatically switching between outputs from VIO and PDR. Experiments were carried out to test and evaluate the proposed PDR-assisted visual integrity monitoring. The sensor suite of experiments consisted of a stereo camera and an inertial measurement unit (IMU). Results were analyzed in detailed and indicated that the proposed system performs better for indoor positioning within an environment that contains low illumination, little background texture information, or few moving objects.

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Multi-UAV formation geometries for cooperative navigation in GNSS-challenging environments

Cited by 51 publications

References 13 publications

Photometric Long-Range Positioning of LED Targets for Cooperative Navigation in UAVs

Photometric Long-Range Positioning of LED Targets for Cooperative Navigation in UAVs

A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications

Pedestrian Dead Reckoning-Assisted Visual Inertial Odometry Integrity Monitoring

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