Segmented SLAM in three‐dimensional environments

Different Terrain Based Navigation systems for underwater vehicles have already been presented, with experimentally validated results and consistent performance. However, these results are mostly based on the use of both high accuracy inertial navigation systems and high quality sonars.This article presents a study on Particle Filter algorithms that cope with peculiarities of Terrain Based Navigation for sensor limited systems. The focus is on the influence on several parameters, namely the process noise, the measurement noise and the number of the particles, and how these can improve the obtained results. Based on the results obtained by simulation, we present some conclusions relevant for the design of future implementation of the algorithms.

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“…Similar measurements models have also commonly used in related areas [8], [9]. A more detailed derivation of this model can be found in [10].…”

Section: B Observation Modelmentioning

confidence: 99%

“…, x [M ] } from an appropriate distribution. If this is the case, then the weighted set of of particles is enough to approximate the system state, and a solution to the to the Minimum Mean Square estimate of the state can be expressed according to (9)…”

Section: Particle Filtermentioning

confidence: 99%

On the use of particle filters for terrain based navigation of sensor-limited AUVs

Melo

Matos

2013

2013 MTS/IEEE OCEANS - Bergen

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“…However, as stated by Thrun et al (2005), a straightforward implementation of this filter for the SLAM problem would be doomed to fail, due to the large number of variables involved in describing a map. Nevertheless, with some adaptations, PF based SLAM algorithms have also been proposed, namely the FastSLAM algorithm by Montemerlo et al (2002), the Distributed Particle SLAM (DP-SLAM) by Parr, (2003, 2004), or the Segmented SLAM by Fairfield et al (2010).…”

Section: Underwater Slammentioning

confidence: 99%

Survey on advances on terrain based navigation for autonomous underwater vehicles

2017

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The autonomy of robotic underwater vehicles is dependent on the ability to perform long-term and long-range missions without need of human intervention. While current state-of-the-art underwater navigation techniques are able to provide sufficient levels of precision in positioning, they require the use of support vessels or acoustic beacons. This can pose limitations on the size of the survey area, but also on the whole cost of the operations. Terrain Based Navigation is a sensor-based navigation technique that bounds the error growth of deadreckoning using a map with terrain information, provided that there is enough terrain variability. An obvious advantage of Terrain Based Navigation is the fact that no external aiding signals or devices are required. Because of this unique feature, terrain navigation has the potential to dramatically improve the autonomy of Autonomous Underwater Vehicles (AUVs). This paper consists on a comprehensive survey on the recent developments for Terrain Based Navigation methods proposed for AUVs. The survey includes a brief introduction to the original Terrain Based Navigation formulations, as well as a description of the algorithms, and a list of the different implementation alternatives found in the literature. Additionally, and due to the relevance, Bathymetric SLAM techniques will also be discussed.

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“…There are different approaches, namely using evidence grid-based submaps (even for 3D) [12,13], feature-based maps [3] or mixing topological and metric information [26]. The common problem is that local maps should be statistically independent.…”

Section: Introductionmentioning

confidence: 99%

Real-time optical SLAM-based mosaicking for unmanned underwater vehicles

Ferreira

Veruggio

Caccia

et al. 2011

Intel Serv Robotics

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This article discusses the possibility of building in real-time a mosaic of the seafloor relying on a simultaneous localization and mapping (SLAM) framework. The goal is to provide an unmanned underwater vehicle with a relatively rough visual map of the seafloor to support basic navigation and context awareness. To achieve that goal, an accurate estimation of the location of the visual landmarks and, in particular, the correct data association when a visual landmark is re-visited by the vehicle are the crucial points. Instead of using a global mosaic, this work uses the combination of a set of local mosaics constructed in the vicinity of the SLAM visual landmarks. The contributions of this article are mainly the use of SURF features, the local mosaics approach and the real-time capability. The use of SURF features allows eliminating false positives in the data association of SLAM visual landmarks. The local mosaics approach is an effective way of correcting the effects of the drift on the mosaic in real time. The main contribution is the real-time capability as it will be seen. The algorithm was tested using a batch of experimental data in typical operating conditions and the results prove the effectiveness of the approach. Electronic supplementary materialThe online version of this article (

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Segmented SLAM in three‐dimensional environments

Cited by 26 publications

References 38 publications

On the use of particle filters for terrain based navigation of sensor-limited AUVs

On the use of particle filters for terrain based navigation of sensor-limited AUVs

Survey on advances on terrain based navigation for autonomous underwater vehicles

Real-time optical SLAM-based mosaicking for unmanned underwater vehicles

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