scholarly journals Self-repelling bipedal exploration process

2021 ◽  
Vol 104 (5) ◽  
Author(s):  
Hor Dashti-N ◽  
M. N. Najafi ◽  
Hyunggyu Park
Keyword(s):  
2008 ◽  
Vol 19 (3) ◽  
pp. 407-420 ◽  
Author(s):  
Philippe Silberzahn ◽  
Christophe Midler

PurposeThe purpose of this study is to examine how firms deal with a situation of true uncertainty about their potential markets and technologies. Specifically, it asks how firms can create products when the corresponding market does not exist.Design/methodology/approachThis paper is based on a longitudinal study of a high‐tech firm, combined with analysis of existing theory in product design and entrepreneurship.FindingsMarkets and products are usually a defining choice made early on by firms in their strategic process. Such a choice guides their development by providing a “stable concept” to which decisions can be related. When markets do not exist yet, however, this approach is not effective. Early choice of products and markets limits firms' flexibility by constraining their ability and willingness to adapt, while fundamental new technical and market information is likely to emerge during the project that will prove the initial assumptions wrong. The paper shows an alternative approach where products and markets actually result from a generic process of products and markets exploration driven by the firm. It is suggested that this approach forms a robust design in that it allows the firm to deal with the uncertainty by simultaneously developing its products and exploring markets, while preserving the flexibility to adapt to the changing environment.Practical implicationsThe practical implication of this paper is to suggest an alternative approach to deliberate planning in high‐tech ventures. With this approach, rather than markets and products, strategy defines a market and technology exploration process.Originality/valueThe paper is original in three ways. It links the product design and market exploration processes in high‐tech firm development; it is based on an in‐depth longitudinal study; and it results from an academic‐practitioner collaborative work.


2012 ◽  
Vol 229-231 ◽  
pp. 495-498
Author(s):  
Hui Xin Liu ◽  
Xian Min Yang ◽  
Cheng Tao Li ◽  
Xiang Cheng

There is a common problem during kill a well, which is how to quickly and accurately control the surface casing pressure according to the requirements for killing a well. A step-by-step exploration process is employed on operation sites. Continuously adjusting throttle valve to acquire surface casing pressure may lead to failure of kill operation because of its long time and low control accuracy. Obviously, if the calculation problems of throttling drawdown can be resolved,the relationship between drawdown and throttle valve opening can be found and the course of explorating can be converted into a straight course.Then the success rate of killing well can be improved. More importantly, this can make automatic controll of surface casing pressure possible. The paper built the calculation method of throttling pressure drop by theoretical analysis and verified the calculation method by adopting it into field test. The result has showed that the calculation method of throttling pressure drop coincides with experimental results and it can be used in engineering practice.


SEG Discovery ◽  
2011 ◽  
pp. 1-23
Author(s):  
James L. Marlatt ◽  
T. Kurt Kyser

ABSTRACT Uranium exploration increased over the past decade in response to an increase in the price of uranium, with more than 900 companies engaged in the global exploration on over 3,000 projects. Major economic discoveries of new uranium orebodies have been elusive despite global exploration expenditures of $3.2 billion USD, with most of the effort in historical uranium districts. The increased effort in exploration with minimal return can be described through the example of a cyclical model based on exploration and discovery in the prolific Athabasca Basin, Saskatchewan. The model incorporates exploration expenditure, quantities of discovered uranium, and the sequence of uranium deposit discoveries to reveal that discovery cycles are epochal in nature and that they are also intimately related to the development and deployment of new exploration technologies. Exploration in the Athabasca Basin can be divided into an early “prospector” phase and the current “model-driven”phase. The future of successful uranium exploration is envisaged as the “innovation exploration” stage in which a paradigmatic shift in the exploration approach will take the industry towards new discoveries by leveraging research and technology development. Effective engagement within the “innovation exploration” paradigm requires that exploration organizations recognize knowledge brokers, and adopt research, development, and technology transfer as a long-term, systematic strategy, including critical definition of exploration targets, identification of innovation frontiers needed, enhanced leadership to accurately portray the research and development imperative and elevation of the status of the research and development effort within the organizational system.


2018 ◽  
Vol 62 (9) ◽  
pp. 1284-1300 ◽  
Author(s):  
Khalil Mohamed ◽  
Ayman El Shenawy ◽  
Hany Harb

Abstract Exploring the environment using multi-robot systems is a fundamental process that most automated applications depend on. This paper presents a hybrid decentralized task assignment approach based on Partially Observable Semi-Markov Decision Processes called HDec-POSMDPs, which are general models for multi-robot coordination and exploration problems in which robots can make their own decisions according to its local data with limited communication between the robot team. In this paper, a variety of multi-robot exploration algorithms and their comparison have been tackled. These algorithms, which have been taken into consideration, are dependent on different parameters. Collectively, there are five metrics maximize the total exploration percentage, minimize overall mission time, reduce the number of hops in the networked robots, reduce the energy consumed by each robot and minimize the number of turns in the path from the start pose cells to the target cells. Therefore, a team of identical mobile robots is used to perform coordination and exploration process in an unknown cell-based environment. The performance of the task depends on the strategy of coordination among the robots involved in the team. Therefore, the proposed approach is implemented, tested and evaluated in MRESim computer simulator, and its performance is compared with different coordinated exploration strategies for different environments and different team sizes. The experimental results demonstrate a good performance of the proposed approach compared to the four existing approaches.


Author(s):  
N. Schüler ◽  
G. Agugiaro ◽  
S. Cajot ◽  
F. Maréchal

<p><strong>Abstract.</strong> The cities in which we live are constantly evolving. The active management of this evolution is referred to as urban planning. The according development process could go in many directions resulting in a large number of potential future scenarios of a city. The planning support system URB<sup>io</sup> adopts interactive optimization to assist urban planners in generating and exploring those various scenarios. As a computer-based system it needs to be able to efficiently handle all underlying data of this exploration process, which includes both methodology-specific and context-specific information. This article describes the work carried out to link URB<sup>io</sup> with a semantic city model. Therefore, two key requirements were identified and implemented: (a) the extension of the CityGML data model to cope with many scenarios by the proposition of the Scenario Application Domain Extension (ADE) and (b) the definition of a data model for interactive optimization. Classes and features of the developed data models are motivated, depicted and explained. Their usability is demonstrated by walking through a typical workflow of URB<sup>io</sup> and laying out the induced data flows. The article is concluded with stating further potential applications of both the Scenario ADE and the data model for interactive optimization.</p>


Author(s):  
H. BARCELONA ◽  
G. PERI ◽  
D. WINOCUR ◽  
A. FAVETTO

The present research explores the Bañitos-Gollete geothermal field located in the Frontal Andes Cordillera over the Pampean flat-slab. We carried out an audiomagnetotelluric survey in order to define the underground geoelectrical structure and to understand the link between the geothermal fluid flow path and the main geological structures. 2-D audiomagnetotelluric models suggest that the deep-rooted N-S fault system controls the geothermal flow path. We propose a conductive heat-driven system, taking into consideration the geologic setting and the supposed low geothermal gradient of this tectonic environment. The mature Na-Cl waters from Gollete and an estimated reservoir temperature of ~140ºC are consistent with this conceptual model. Further investigations are required to assess the geothermal potential of the study area, and the present work likely represents only the first but necessary step in the exploration process.


2019 ◽  
Author(s):  
Robert Krueger ◽  
Johanna Beyer ◽  
Won-Dong Jang ◽  
Nam Wook Kim ◽  
Artem Sokolov ◽  
...  

AbstractFacetto is a scalable visual analytics application that is used to discover single-cell phenotypes in high-dimensional multi-channel microscopy images of human tumors and tissues. Such images represent the cutting edge of digital histology and promise to revolutionize how diseases such as cancer are studied, diagnosed, and treated. Highly multiplexed tissue images are complex, comprising 109or more pixels, 60-plus channels, and millions of individual cells. This makes manual analysis challenging and error-prone. Existing automated approaches are also inadequate, in large part, because they are unable to effectively exploit the deep knowledge of human tissue biology available to anatomic pathologists. To overcome these challenges, Facetto enables a semi-automated analysis of cell types and states. It integrates unsupervised and supervised learning into the image and feature exploration process and offers tools for analytical provenance. Experts can cluster the data to discover new types of cancer and immune cells and use clustering results to train a convolutional neural network that classifies new cells accordingly. Likewise, the output of classifiers can be clustered to discover aggregate patterns and phenotype subsets. We also introduce a new hierarchical approach to keep track of analysis steps and data subsets created by users; this assists in the identification of cell types. Users can build phenotype trees and interact with the resulting hierarchical structures of both high-dimensional feature and image spaces. We report on use-cases in which domain scientists explore various large-scale fluorescence imaging datasets. We demonstrate how Facetto assists users in steering the clustering and classification process, inspecting analysis results, and gaining new scientific insights into cancer biology.


Author(s):  
Ravi Kulan Rathnam ◽  
Andreas Birk

AbstractAn algorithm for distributed exploration in 3D is presented which always keeps the robots within communication range of each other. The method is based on a greedy optimization strategy that uses a heuristic utility function. This makes it computationally very efficient but it can also lead to local minimums; but related deadlocks can be easily detected during the exploration process and there is an efficient strategy to recover from them. The exploration algorithm is integrated into a complete control infrastructure for Autonomous Underwater Vehicles (AUV) containing sensors, mapping, navigation, and control of actuators. The algorithm is tested in a high fidelity simulator which takes into account the dynamics of the robot, and simulates the required sensors. The effect of the communication range and the number of robots on the algorithm is investigated.


2021 ◽  
pp. 36-50
Author(s):  
O. V. Elisheva ◽  
K. A. Sosnovskikh

In order to improve the efficiency of exploration drilling at various greenfield license areas owned by Rosneft Oil Company, Tyumen Petroleum Scientific Center LLC has been actively developing and implementing various innovative technologies in recent years that allow increasing the probability of discovering new hydrocarbon deposits. One of such approaches is the use of different methods based on the principles of fractality of geological objects. The article presents the results of using the fractal analysis method to solve one of the applied problems of oil and gas geology, namely, the correction of the boundaries of facies zones on facies maps, which are the basis for constructing risk maps for the "reservoir". It is shown that the boundaries of the facies zones on facies maps, built mainly on seismic data and a limited amount of materials from exploration drilling, have a large variability. The found statistical relationship between the distribution of the total reservoir thicknesses in different facies zones and the fractal dimension of the traps made it possible to correct facies and risk maps.


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