Marine Applications of the Fast Marching Method

Garrido, Santiago; Álvarez, David; Moreno, Lourdes

doi:10.3389/frobt.2020.00002

Cited by 15 publications

(13 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An improved anisotropic fast marching method using a multi-layered fast marching was proposed by Song, Liu & Bucknall (2017), which combines different environmental factors and provides interesting results. In addition to the global path planning, the FMM-based methods also show potential in collision avoidance of USVs (Wang, Jin & Er, 2019;Garrido, Alvarez & Moreno, 2020). These successful studies have demonstrated the potential of FMM-based methods in global path planning of USVs.…”

Section: Introductionmentioning

confidence: 90%

“…FMM-based methods have been widely used in path planning applications (Gómez et al, 2013;Amorim & Ventura, 2014;Alvarez et al, 2015;González et al, 2016). Marine applications based on FMM were introduced by Garrido, Alvarez & Moreno (2020). Interesting modifications for the FM 2 method have been performed, and the FMM has been subjected to a vector field considering the effects of several vector variables such as wind flow or water currents (Garrido, Alvarez & Moreno, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Marine applications based on FMM were introduced by Garrido, Alvarez & Moreno (2020). Interesting modifications for the FM 2 method have been performed, and the FMM has been subjected to a vector field considering the effects of several vector variables such as wind flow or water currents (Garrido, Alvarez & Moreno, 2020). In addition, studies on path following and obstacle avoidance and formations have also been conducted using FMM (Garrido, Alvarez & Moreno, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Interesting modifications for the FM 2 method have been performed, and the FMM has been subjected to a vector field considering the effects of several vector variables such as wind flow or water currents (Garrido, Alvarez & Moreno, 2020). In addition, studies on path following and obstacle avoidance and formations have also been conducted using FMM (Garrido, Alvarez & Moreno, 2020). USV formation path planning has also been performed by Liu & Bucknall (2015) and Tan et al (2020), and an angle-guidance FM 2 method has been used for the Springer USV to make the generated path compliant with the dynamics and orientation restrictions of USVs (Liu & Bucknall, 2016;Liu, Bucknall & Zhang, 2017).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Rapid global path planning algorithm for unmanned surface vehicles in large-scale and multi-island marine environments

Wang

Zhang

Jin

et al. 2021

PeerJ Computer Science

View full text Add to dashboard Cite

A global path planning algorithm for unmanned surface vehicles (USVs) with short time requirements in large-scale and complex multi-island marine environments is proposed. The fast marching method-based path planning for USVs is performed on grid maps, resulting in a decrease in computer efficiency for larger maps. This can be mitigated by improving the algorithm process. In the proposed algorithm, path planning is performed twice in maps with different spatial resolution (SR) grids. The first path planning is performed in a low SR grid map to determine effective regions, and the second is executed in a high SR grid map to rapidly acquire the final high precision global path. In each path planning process, a modified inshore-distance-constraint fast marching square (IDC-FM2) method is applied. Based on this method, the path portions around an obstacle can be constrained within a region determined by two inshore-distance parameters. The path planning results show that the proposed algorithm can generate smooth and safe global paths wherein the portions that bypass obstacles can be flexibly modified. Compared with the path planning based on the IDC-FM2 method applied to a single grid map, this algorithm can significantly improve the calculation efficiency while maintaining the precision of the planned path.

show abstract

Section: Introductionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Rapid global path planning algorithm for unmanned surface vehicles in large-scale and multi-island marine environments

Wang

Zhang

Jin

et al. 2021

PeerJ Computer Science

View full text Add to dashboard Cite

show abstract

“…The distance calculated at each iteration is compared with the distance of each previous iteration. A priority queue is generated where the shortest distances are given priority [75]. An update in distance is defined as:…”

Section: Geodesic Distancementioning

confidence: 99%

Modeling Two-Person Segmentation and Locomotion for Stereoscopic Action Identification: A Sustainable Video Surveillance System

et al. 2021

View full text Add to dashboard Cite

Due to the constantly increasing demand for automatic tracking and recognition systems, there is a need for more proficient, intelligent and sustainable human activity tracking. The main purpose of this study is to develop an accurate and sustainable human action tracking system that is capable of error-free identification of human movements irrespective of the environment in which those actions are performed. Therefore, in this paper we propose a stereoscopic Human Action Recognition (HAR) system based on the fusion of RGB (red, green, blue) and depth sensors. These sensors give an extra depth of information which enables the three-dimensional (3D) tracking of each and every movement performed by humans. Human actions are tracked according to four features, namely, (1) geodesic distance; (2) 3D Cartesian-plane features; (3) joints Motion Capture (MOCAP) features and (4) way-points trajectory generation. In order to represent these features in an optimized form, Particle Swarm Optimization (PSO) is applied. After optimization, a neuro-fuzzy classifier is used for classification and recognition. Extensive experimentation is performed on three challenging datasets: A Nanyang Technological University (NTU) RGB+D dataset; a UoL (University of Lincoln) 3D social activity dataset and a Collective Activity Dataset (CAD). Evaluation experiments on the proposed system proved that a fusion of vision sensors along with our unique features is an efficient approach towards developing a robust HAR system, having achieved a mean accuracy of 93.5% with the NTU RGB+D dataset, 92.2% with the UoL dataset and 89.6% with the Collective Activity dataset. The developed system can play a significant role in many computer vision-based applications, such as intelligent homes, offices and hospitals, and surveillance systems.

show abstract

The stochastic simulation of karst conduit network structure using anisotropic fast marching, and its application to a geologically complex alpine karst system

et al. 2022

View full text Add to dashboard Cite

Anisotropic fast-marching algorithms are computationally efficient tools for generating realistic maps of karst conduit networks, constrained by both the spatial extent and the orientation of karstifiable geologic units. Existing models to generate conduit network maps are limited either by high computational requirements (for chemistry-based models) or by their inability to incorporate the effects of elevation and orientation gradients (for isotropic fast-marching models). The new anisotropic fast-marching approach described here provides a significant improvement, though it imitates rather than reproduces actual speleogenetic processes. It can rapidly generate a stochastic ensemble of plausible networks from basic geologic information, which can also be used as input to karst-appropriate flow models. This paper introduces an open-source, easy-to-use implementation through the Python package pyKasso, then describes its application to a well-mapped geologically complex long-term study site: the Gottesacker alpine karst system (Germany/Austria). Groundwater flow in this system is exceptionally well understood from speleological investigations and tracer tests. Conduit formation primarily occurs at the base of the karst aquifer, following plunging synclines. Although previous attempts to reproduce the conduit network at this site yielded implausible network maps, pyKasso quickly generated networks faithful to the known conduit system. However, the model was only able to generate these realistic networks when the inlet-outlet connections of the system were correctly assigned, highlighting the importance of pairing modeling efforts with field tracer tests. Therefore, a model ensemble method is also presented, to optimize field efforts by identifying the most informative tracer tests to perform.

show abstract

Marine Applications of the Fast Marching Method

Cited by 15 publications

References 19 publications

Rapid global path planning algorithm for unmanned surface vehicles in large-scale and multi-island marine environments

Rapid global path planning algorithm for unmanned surface vehicles in large-scale and multi-island marine environments

Modeling Two-Person Segmentation and Locomotion for Stereoscopic Action Identification: A Sustainable Video Surveillance System

The stochastic simulation of karst conduit network structure using anisotropic fast marching, and its application to a geologically complex alpine karst system

Contact Info

Product

Resources

About