Khalid Mahmood Arif

Indoor localization of mobile robot with visible light communication

This paper focuses on the implementation of visible light communication (VLC) with an autonomous mobile robot to provide indoor localization. Recent research on VLC, mostly in the form of simulations, offers the opportunity to conduct real life experiments and test the theory. Accurate indoor positioning is achieved by employing multi-frequency method with received signal strength (RSS) to calculate the distance of the robot from each LED installed above the robot in a plane parallel to the plane of the robot base. Multi-frequency method consists of each LED transmitting its location ID at a different frequency. It is demonstrated that the receiver is able to separate each location ID from simultaneous data transmission with a bandpass filter.

Limit of detection for a bead-based diffraction biosensor

Diffraction-based biosensors that rely on optical scattering are a sensitive approach for biomolecular detection. We present a Mie surface double-interaction computer study of the in situ assembly of bead-based diffraction gratings on a gold substrate. The limit of detection for a system having 26 stripes is calculated to be approximately 25 beads in total, or approximately one bead per stripe in an immunoassay experiment. This sensitivity limit is orders of magnitude better than label-free molecular sensors, and is consistent with high-speed scanning for high-throughput assays.

Bio-inspired multitasking robotic gripper design and development

The purpose of this study is to develop a bird-like claw mechanism that allows amphibious motion for walking, swimming and grasping on land. The inspiration for this work came from birds, which are capable of moving on land and grasping objects, and able to navigate through water. The motion of the bird foot has not been studied in detail before hence there is an opportunity to advance work in this area, and design a bio-inspired mechanism. This paper demonstrates the viability of the use of the claw mechanism for grasping objects compared to the grasping capabilities of the human hand. This claw model has only half the number of joints of a human hand therefore offers lower cost and easier management. Its smaller palm size facilitates the handling of small items. A hardware scaled model of a bird foot is designed to show how simple manipulation tasks can be done.

Feature extraction for moving object detection in a non-stationary background

Classification of moving objects in a non-stationary background has become a vast area of study, which is used in various applications where neither the background nor the foreground is stationary. Feature detection becomes an important part to detect moving objects when the background itself is also moving. Harris corner detection, SIFT (Scale Invariant Feature Transform) and SURF (Speeded-Up Robust Features) are three most commonly used feature detection algorithms. Clustering of feature points using block-based k-means clustering along with feature detection are used to distinguish moving objects from the background. This paper presents a study among various methods that were evaluated and compared on robustness, amount of points detected, computation time and overall performance. The simulations were carried out in MATLAB.

Efficient robotic SLAM by fusion of RatSLAM and RGBD-SLAM

This paper presents a novel method to improve the robotic SLAM by fusing aspects from the RGBD-SLAM and RatSLAM methods. The proposed solution takes the 3D feature representations of the environment much like the RGBD-SLAM system but instead of creating a voxel map, it creates a grid map taking elements from the RatSLAM system. The resulting integration of SLAM methods eliminates the need for a continuous stream of images as required in RGBD-SLAM and thus overcomes the problem of ambiguous data normally generated by featureless surface such as repeating wall patterns. The proposed solution is implemented on a Pioneer 3-DX mobile robot using Kinect sensor. The results show that the proposed method can successfully conduct SLAM in an efficient manner.

Mobile machine vision development for urine patch detection

This paper discusses the research of integrating and implementing current technologies to detect urine patches. Currently, cattle urine is damaging the agricultural industry and poses an increasing threat to the environment. Farmers invest a lot of money treating urine patches and nitrate leaches into waterways, which pollutes drinking water and causes fish to die. Current methods are slow and inefficient in detecting urine patches across large areas of land. The proposed method comprises of mounting a smartphone onto a quadcopter and using the smartphones camera to run OpenCV image processing libraries to visually detect urine patches. The quadcopter serves as a fast method of moving the smartphone, at a fixed height from the ground, to survey and detect urine patches. When a urine patch is detected, its GPS coordinates are obtained, from the smartphones GPS sensor, and they are sent to the farmer so the patches can be located for treatment.

Particle image velocimetry study of displacement field in granular continua under axisymmetric conditions

In this paper we study the characteristics of displacement field during installation of a model pile in granular media using particle image velocimetry (PIV). A steel pile of 12.7 mm width was driven to a depth of 120 mm in silica sand of 0.6 mm mean particle size in axisymmetric condition. The chamber for the sand was fabricated out of transparent acrylic glass to allow high resolution imaging from front side under diffused illumination condition. Instron material testing system was utilized to drive the pile into the soil with controlled speed while a custom-built imaging system recorded the images for offline processing with PIV algorithms. Before application of the technique to the model pile, PIV parameters were also optimized through a simple translation test. Results for displacement as well as strain field obtained using finite element post-processing are appended as evidence of impact of this study.

Size optimization and fatigue study of Ti-6Al-4V membranes for long-term ICP measurement

Drift in capacitive membrane pressure sensors is a serious concern in the long-term intracranial pressure (ICP) measurements. The major cause of drift is attributed to mechanical fatigue of the flexible membrane, which deflects in response to the applied pressure. Optimization of the membrane parameters, particularly size, could help in improving the fatigue life and overall performance of the membrane pressure sensors. In this paper, Ti-6Al-4V, grade 5, solution treated and annealed, biocompatible membrane has been numerically modeled for obtaining the overall desired size. In addition, multiaxial critical plane high cycle fatigue model was incorporated into the design to compute fatigue usage factors and cycles to failure of the membrane. With a diameter of 100 μm, thickness of 4 μm, the optimized membrane exhibited a life of about 100 million cycles to failure.

Simulation of nanoparticle enhanced diffraction grating biosensor using DDA

We present the discrete dipole approximation (DDA) simulation of light scattering from bead enhanced grating to determine the relationship between the number of beads forming the grating and diffraction intensities of first and zero orders. The models of grating are prepared by volume slicing and image processing while the spatial locations of the beads are randomly computed using discrete probability distribution. The effect of bead reduction on far-field scattering of 632.8 nm incident field, from fully occupied gratings to very coarse gratings, are studied for various bead materials. The results of simulations show excellent qualitative similarities with published experimental observations and establish that bead-based grating may be used for rapid detection of small amounts of biomolecules.

Nanoparticle light scattering on interferometric surfaces

We present a model based on Mie Surface Double Interaction (MSDI) to explore bead-based detection mechanisms using imaging and scanning. The application goal of this work is to explore the trade-offs between the sensitivity and throughput among various detection methods. Experimentally we use thermal oxide on silicon to establish and control surface interferometric conditions. Surface-captured gold beads are detected using Molecular Interferometric Imaging (MI2) and Spinning-Disc Interferometry (SDI).