Robust range-only SLAM for aerial vehicles

Fabresse, Felipe R.; Caballero, Fernando; Maza, Iván; Ollero, A.

doi:10.1109/icuas.2014.6842320

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…An example of the pre-filtering [46] results for range-only observations between robot (node 25) and node 6 is shown in Fig. 8 for a Nanotron radio-based range-only sensor in a real indoor experiment.…”

Section: Resultsmentioning

confidence: 99%

An efficient approach for undelayed range-only SLAM based on Gaussian mixtures expectation

Fabresse

Caballero

Maza

et al. 2018

Robotics and Autonomous Systems

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Section: Resultsmentioning

confidence: 99%

An efficient approach for undelayed range-only SLAM based on Gaussian mixtures expectation

Fabresse

Caballero

Maza

et al. 2018

Robotics and Autonomous Systems

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“…Range measurements were limited to 30 meters as the number of outliers increase linearly with the distance between the sensors. A pre-filtering algorithm have 1 been used in all experiments for range observations using the algorithm described in [15].…”

Section: B Real Experiments Involving Real Vehicles and Range-only Smentioning

confidence: 99%

Decentralized simultaneous localization and mapping for multiple aerial vehicles using range-only sensors

Fabresse

Caballero

Ollero

2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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This paper presents an approach for decentralized range-only simultaneous localization and mapping (RO-SLAM) of a network of aerial vehicles and a set of static range-only sensors deployed in the environment. The paper makes use of a multi-hypothesis framework developed by the authors [1] in order to deal with the multiple hypotheses that are present in the early stages of the undelayed RO-SLAM, this paper extends the approach to consider the integration of landmark estimations provided by other aerial vehicles nearby the robot. The method will enable a significant reduction in the convergence time needed to remove wrong localization hypotheses for every range-only landmark and, as a results, a map with improved accuracy. The proposed approach is validated first in simulations and later on with real experiments involving real range-only sensors and two unmanned aerial vehicles.

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“…Blanco et al [ 46 ] first proposed a Gaussian mixture model (GMM)-based initialization strategy, which provides accurate results but makes the integration of inter-beacon measurements impossible as each beacon is inserted in an independent EKF. On the basis of this research, Felipe et al [ 47 ] proposed a centralized EKF-based initialization framework, which allowed the integration of inter-beacon measurements, and they enhanced it with a outlier rejection filter [ 48 , 49 ]. Geneve et al [ 50 ] proposed a short-delayed composite initialization method based on Euclidean parameterization and a two-hypothesis GMM, which showed a lower computational cost.…”

Section: Introductionmentioning

confidence: 99%

A Distributed Radio Beacon/IMU/Altimeter Integrated Localization Scheme with Uncertain Initial Beacon Locations for Lunar Pinpoint Landing

Luo³

et al. 2020

Sensors

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As a growing number of exploration missions have successfully landed on the Moon in recent decades, ground infrastructures, such as radio beacons, have attracted a great deal of attention in the design of navigation systems. None of the available studies regarding integrating beacon measurements for pinpoint landing have considered uncertain initial beacon locations, which are quite common in practice. In this paper, we propose a radio beacon/inertial measurement unit (IMU)/altimeter localization scheme that is sufficiently robust regarding uncertain initial beacon locations. This scheme was designed based on the sparse extended information filter (SEIF) to locate the lander and update the beacon configuration at the same time. Then, an adaptive iterated sparse extended hybrid filter (AISEHF) was devised by modifying the prediction and update stage of SEIF with a hybrid-form propagation and a damping iteration algorithm, respectively. The simulation results indicated that the proposed method effectively reduced the error in the position estimations caused by uncertain beacon locations and made an effective trade-off between the estimation accuracy and the computational efficiency. Thus, this method is a potential candidate for future lunar exploration activities.

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Robust range-only SLAM for aerial vehicles

Cited by 4 publications

References 15 publications

An efficient approach for undelayed range-only SLAM based on Gaussian mixtures expectation

An efficient approach for undelayed range-only SLAM based on Gaussian mixtures expectation

Decentralized simultaneous localization and mapping for multiple aerial vehicles using range-only sensors

A Distributed Radio Beacon/IMU/Altimeter Integrated Localization Scheme with Uncertain Initial Beacon Locations for Lunar Pinpoint Landing

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