A Graph SLAM algorithm along with an object detection module based on deep learning are employed in order to generate an estimated map of a previously unexplored area. A ZED camera, which provides RGB and depth images, is mounted on a ground vehicle which is moved in the area to be explored in order to collect the required data for mapping. While maneuvering in the environment, the wheel encoders embedded in the ground vehicle are used to estimate the robot's position using dead reckoning.
Robotic Urban Search and Rescue (USAR) is a challenging yet promising research area which has potential applications as proven throughout the rescue and recovery operations in real-world disasters. The main challenge for rescuers is to adapt to the unique conditions of the indoor USAR environment including the inflexible navigation and the harsh conditions. In this paper, we study the different approaches used for exploration in an indoor unstructured environment and propose an efficient exploration method to enhance the existing state of the art exploration strategies. The proposed method considers in the exploration algorithm the extracted contextual information gathered from images. The comparison between the state of the art exploration method is provided.
This paper experimentally illustrates the modeling and simulation of the Lynxmotion Robot, using the robotics toolbox under MATLAB. This project is part of a graduate course on robotics. The main objective of this paper is to control the robot to perform a pick and place task. The task is simulated under MATLAB, where the robot picks objects from known positions and stacks them in target positions. The command is then sent to the robot to execute this task. Furthermore, the robot, with the aid of a vision system, is programmed to work as an autonomous robotic arm that picks up colored objects, and then places them in different positions, based on their colors.
In this paper, the objective is to present the Rapidly-Exploring Random Tree Star (RRT*) algorithm both in simulation and application. The purpose of this algorithm is to generate probabilistically complete and cost-effective paths in static or dynamic environments. This algorithm is implemented to drive a Kobuki mobile robot using MATLAB.
Integration of multi-data sources (static and dynamic) is vital to the understanding of the mechanisms of fluid flow present in a given reservoir. Calibration of geologic-based models (conditioned by static data) to flow-related data (well test and production data) can dramatically reduce the uncertainty in reservoir models. In this work, we present a new development to further reduce the uncertainty in the characterization of fracture properties (e.g., orientation, conductivity, aperture, length and density) from well test pressure responses (e.g., permeabilitythickness product, storativity, and interporosity). The optimization problem is addressed using a direct search method. A novel multi-level genetic algorithm is developed to find the optimum solution space of the fracture properties by minimizing the error in a new multi-objective function. The proposed algorithm was benchmarked against the industrial software FracaFlow?. Our results clearly show further reduction of uncertainties in fracture property estimation compared to FracaFlow?.
This study mainly puts forward a new analytical trilinear dual-porosity & dual-permeability flow mode for the multi-fractured horizontal well (MFHW) in the naturally fractured reservoir (NFR) based on the trilinear dual-porosity flow model[1]. This model is an upgraded trilinear flow model, a simple but versatile one to integrate horizontal-well-related parameters and petrophysical characteristics of the naturally fractured reservoir, including wellbore storage, chocking skin factor, intrinsic properties of matrix and fracture systems, and even different properties of the stimulated area and the unstimulated area. The model incorporates a dual-permeability model for the stimulated flow region and a dual-porosity model for the unstimulated flow region respectively. In common sense, the traditional flow model for the fractured horizontal well with the line-source solution is computationally intensive and time-consuming, while this model makes itself a practical alternative with computational convenience and also incorporates most of the distinct flow patterns identical as the line-source solution does. The new trilinear flow model would show a field-friendly way to analyze the transient pressure behavior of the multi-fractured horizontal well in the reservoir with well-developed natural fractures.
The aim of this research was to investigate the mechanisms leading to enhanced oil recovery in limestones by simple chemical manipulation of the injection water, while taking the equation of capillary number into consideration. A main objective of this study was to gain insights regarding the quantification of wettability alteration, as the existing equation fails to describe how wettability alteration could lead to enhanced oil recovery in non-water wet plugs.The existing mathematical description of wettability " Cosine function" into the capillary number equation poses a dilemma that hinders the up-scaling of low salinity and smart water flooding processes. As per the results of this research, there is strong evidence that wettability alteration by means of electrical double layer expansion is the mechanism that leads to additional oil recovery in some cases In all tests, only the brines that triggered increased electrostatic repulsion between the two interfaces, resulted in incremental oil recovery.
He-3 detectors are considered as the main component of most of the neutron detection system in various nuclear fields because of their high thermal neutron cross section. Due to the worldwide shortage of He-3 gas after 2009 and the consequent huge price increase, many researchers directed their efforts to find an efficient replacement. In this work an alternative neutron detection setup is introduced and modeled. The setup is composed of a NaI detector covered with a thin layer of boron. For comparison, common neutron detectors like He-3 and BF3 are also modeled. The results show a good sensitivity of the three detectors when exposed to various neutron flux distributions with a higher efficiency of boron-lined NaI detector than He-3 and BF3. An additional benefit is the ability of the boron-lined NaI detector to detect gamma rays from the surrounding medium.
in this paper, cavities were etched in SiO? over Si substrate and then graphene film was transferred forming the graphene membrane over the cavity. Raman spectroscopy of graphene on top of cavities showed significant redshift in the 2D band (0.14 cm?? per 1?m of cavity), because of the elongation of the carbon-carbon bonds. This indicates the feasibility of using graphene membrane as a strain sensor.
In this paper, an alternative method of fabricating microfluidic channels is presented. Microfluidic channels have an array of applications including drug delivery, lab-on-a-chip, fluid and gas sensing. However, the current methods to fabricate these channels involve processes and materials that are not compatible to the state-of-the-art CMOS process flow, making them expensive and unviable for on-chip integration and hence limiting their applications. This work presents an alternative approach to fabricate microfluidic channels that uses materials and processes commonly used in CMOS processes. The proposed microfluidic channel design is based on silicon nitride, and requires few deposition and etching steps, and only two lithography steps, simplifying the fabrication substantially and opening new avenues for the use of microfluidic channels in various applications.
