Potential Field Methods to Investigate the Source of Hydrocarbon Contamination in Sharm El-Maya

2013 ◽  
Vol 24 (1) ◽  
pp. 1-17 ◽  
Author(s):  
A Morsy ◽  
A Rashed ◽  
N El.Masry ◽  
A Soliman
Keyword(s):  
Potential Field ◽  
Hydrocarbon Contamination ◽  
Field Methods

Crustal Structure of the Southern Portuguese Margin - Constraints from Potential Field Methods

2015 ◽  
Author(s):  
A. Ramos ◽  
L. Cascone ◽  
A. Olaiz ◽  
O. Fernández ◽  
A. Sánchez de la Muela ◽  
...  
Keyword(s):  
Crustal Structure ◽  
Potential Field ◽  
Field Methods

Modified Newton's method applied to potential field based navigation for nonholonomic robots in dynamic environments

Robotica ◽  
2008 ◽  
Vol 26 (3) ◽  
pp. 285-294 ◽  
Author(s):  
Jing Ren ◽  
Kenneth A. McIsaac ◽  
Rajni V. Patel
Keyword(s):  
Newton’S Method ◽  
Potential Field ◽  
Newton's Method ◽  
Dynamic Environment ◽  
Dynamic Environments ◽  
Field Methods ◽  
Control Laws ◽  
Nonholonomic Robots ◽  
Modified Newton’S Method ◽  
Speed Up

SUMMARYThis paper is to investigate inherent oscillations problems of Potential Field Methods (PFMs) for nonholonomic robots in dynamic environments. In prior work, we proposed a modification of Newton's method to eliminate oscillations for omnidirectional robots in static environment. In this paper, we develop control laws for nonholonomic robots in dynamic environment using modifications of Newton's method. We have validated this technique in a multirobot search-and-forage task. We found that the use of the modifications of Newton's method, which applies anywhere C2 continuous navigation functions are defined, can greatly reduce oscillations and speed up robot's movement, when compared to the standard gradient approaches.

High-speed navigation of unmanned ground vehicles on uneven terrain using potential fields

Robotica ◽  
2007 ◽  
Vol 25 (4) ◽  
pp. 409-424 ◽  
Author(s):  
Shingo Shimoda ◽  
Yoji Kuroda ◽  
Karl Iagnemma
Keyword(s):  
Potential Field ◽  
High Speed ◽  
Longitudinal Velocity ◽  
Unmanned Ground Vehicles ◽  
Performance Bounds ◽  
Ground Vehicles ◽  
Computationally Efficient ◽  
Field Methods ◽  
Local Maxima ◽  
Natural Terrain

SUMMARYMany applications require unmanned ground vehicles (UGVs) to travel at high speeds on sloped, natural terrain. In this paper, a potential field-based method is proposed for UGV navigation in such scenarios. In the proposed approach, a potential field is generated in the two-dimensional “trajectory space” of the UGV path curvature and longitudinal velocity. In contrast to traditional potential field methods, dynamic constraints and the effect of changing terrain conditions can be easily expressed in the proposed framework. A maneuver is chosen within a set of performance bounds, based on the local potential field gradient. It is shown that the proposed method is subject to local maxima problems, rather than local minima. A simple randomization technique is proposed to address this problem. Simulation and experimental results show that the proposed method can successfully navigate a small UGV between predefined waypoints at speeds up to 7.0 m/s, while avoiding static hazards. Further, vehicle curvature and velocity are controlled during vehicle motion to avoid rollover and excessive side slip. The method is computationally efficient, and thus suitable for onboard real-time implementation.

Data analysis of potential field methods using geostatistics

Geophysics ◽  
2017 ◽  
Vol 82 (2) ◽  
pp. G35-G44 ◽  
Author(s):  
Pejman Shamsipour ◽  
Michel Chouteau ◽  
Denis Marcotte
Keyword(s):  
Data Analysis ◽  
Computational Complexity ◽  
Potential Field ◽  
Field Data ◽  
Regular Grid ◽  
Field Methods ◽  
Potential Field Data ◽  
Spatial Methods ◽  
Geostatistical Methods ◽  
Factorial Kriging

Processing of potential field data is commonly done by spectral methods because of their low computational complexity. However, we have studied some geostatistical methods to process the potential field data, and we find the advantages of using these spatial methods. First, we investigate transformation of data by kriging using a gravimetric model of covariance, we compare this approach with the spectral method, and we find its advantage when the data were sparse and not on a regular grid using a synthetic example as well as a field data example. Then, we use factorial kriging for noise reduction and separation of the regional and residual components. This method does not have some of the practical limitations that the spectral-based methods encounter. Finally, we determine the flexibility of interpolation using nonstationary covariances.

Integrated Potential Field Methods – West Siberian Reservoir Complex Case Study

2020 ◽  
Author(s):  
A. Volkova ◽  
V. Merkulov ◽  
F. Grabovskaya
Keyword(s):  
Potential Field ◽  
Complex Case ◽  
Field Methods
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