Development of Roller-Based Interior Wall Painting Robot

This paper describes the development of an autonomous robot for painting the interior walls of buildings. The robot consists of a painting arm with an end effector roller that scans the walls vertically and a mobile platform to give horizontal feed to paint the whole area of the wall. The painting arm has a planar twolink mechanism with two joints. Joints are driven from a stepping motor through a ball screw-nut mechanism. Four ultrasonic sensors are attached to the mobile platform and used to maintain a certain distance from the facing wall and to avoid collision with side walls. When settled on adjusted distance from the wall, the controller starts the painting process autonomously. Simplicity, relatively low weight and short painting time were considered in our design. Different modules constituting the robot have been separately tested then integrated. Experiments have shown successfulness of the robot in its intended tasks.

Data-driven ASIC for Multichannel Sensors

An approach and its implementation in 0.18 m CMOS process of the multichannel ASIC for capacitive (up to 30 pF) sensors are described in the paper. The main design aim was to study an analog data-driven architecture. The design was done for an analog derandomizing function of the 128 to 16 structure. That means that the ASIC structure should provide a parallel front-end readout of 128 input analog sensor signals and after the corresponding fast commutation with appropriate arbitration logic their processing by means of 16 output chains, including analog-to-digital conversion. The principal feature of the ASIC is a low power consumption within 2 mW/channel (including a 9-bit 20Ms/s ADC) at a maximum average channel hit rate not less than 150 kHz.

Two Wheels Balancing Robot with Line Following Capability

This project focuses on the development of a line follower algorithm for a Two Wheels Balancing Robot. In this project, ATMEGA32 is chosen as the brain board controller to react towards the data received from Balance Processor Chip on the balance board to monitor the changes of the environment through two infra-red distance sensor to solve the inclination angle problem. Hence, the system will immediately restore to the set point (balance position) through the implementation of internal PID algorithms at the balance board. Application of infra-red light sensors with the PID control is vital, in order to develop a smooth line follower robot. As a result of combination between line follower program and internal self balancing algorithms, we are able to develop a dynamically stabilized balancing robot with line follower function.

Kinematic Modelling and Maneuvering of A 5-Axes Articulated Robot Arm

This paper features the kinematic modelling of a 5-axis stationary articulated robot arm which is used for doing successful robotic manipulation task in its workspace. To start with, a 5-axes articulated robot was designed entirely from scratch and from indigenous components and a brief kinematic modelling was performed and using this kinematic model, the pick and place task was performed successfully in the work space of the robot. A user friendly GUI was developed in C++ language which was used to perform the successful robotic manipulation task using the developed mathematical kinematic model. This developed kinematic model also incorporates the obstacle avoiding algorithms also during the pick and place operation.

SWNT Sensors for Monitoring the Oxidation of Edible Oils

There are several means to measure the oxidation of edible oils, such as the acid value, the peroxide value, and the anisidine value. However, these means require large quantities of reagents and are time-consuming tasks. Therefore, a more convenient and time-saving way to measure the oxidation of edible oils is required. In this report, an edible oil condition sensor was fabricated by using single-walled nanotubes (SWNT). In order to test the sensor, oxidized edible oils, each one at a different acid value, were prepared. The SWNT sensors were immersed into these oxidized oils and the resistance changes in the sensors were measured. It was found that the conductivity of the sensors decreased as the oxidation level of oil increased. This result suggests that a change of the oil components induced by the oxidation process in edible oils is related to the conductivity change in the SWNT sensor.

Minimizing of Target Localization Error using Multi-robot System and Particle Filters

In recent years a number of applications with multirobot systems (MRS) is growing in various areas. But their design is in practice often difficult and algorithms are proposed for the theoretical background and do not consider errors and noise in real conditions, so they are not usable in real environment. These errors are visible also in task of target localization enough, when robots try to find and estimate the position of the target by the sensors. Localization of target is possible also with one robot but as it was examined target finding and localization with group of mobile robots can estimate the target position more accurately and faster. The accuracy of target position estimation is made by cooperation of MRS and particle filtering. Advantage of usage the MRS with particle filtering was tested on task of fixed target localization by group of mobile robots.

2D-Modeling with Lego Mindstorms

The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Highly Flexible Modularized Sensor Platform

Sensors have been used in various kinds of academic fields and applications. In this article, we propose the idea of modularized sensors that combine multiple sensor modules into a unique sensor. We divide a sensor into several units according to functionalities. Each unit has different sensor modules, which share the same type of connectors and can be serially and arbitrarily connected each other. A user can combine different sensor modules into a sensor platform according to requirements. Compared with current modularized sensors, the proposed sensor platform is highly flexible and reusable. We have implemented the prototype of the proposed sensor platform, and the experimental results show the proposed platform can work correctly.

Source Direction Detection based on Stationary Electronic Nose System

Electronic nose (array of chemical sensors) are widely used in food industry and pollution control. Also it could be used to locate or detect the direction of the source of emission odors. Usually this task is performed by electronic nose (ENose) cooperated with mobile vehicles, but when a source is instantaneous or surrounding is hard for vehicles to reach, problem occurs. Thus a method for stationary ENose to detect the direction of the source and locate the source will be required. A novel method which uses the ratio between the responses of different sensors as a discriminant to determine the direction of source in natural wind surroundings is presented in this paper. The result shows that the method is accurate and easily to be implemented. This method could be also used in movably, as an optimized algorithm for robot tracking source location.

Robust Integrated Navigation of a Low Cost System

Robust nonlinear integrated navigation of GPS and low cost MEMS is a hot topic of research these days. A robust filter is required to cope up with the problem of unpredictable discontinuities and colored noises associated with low cost sensors. H∞ filter is previously used in Extended Kalman filter and Unscented Kalman filter frame. Unscented Kalman filter has a problem of Cholesky matrix factorization at each step which is a very unstable operation. To avoid this problem in this research H∞ filter is designed in Square root Unscented filter framework and found 50% more robust towards increased level of colored noises.

Multiple Sensors and JPDA-IMM-UKF Algorithm for Tracking Multiple Maneuvering Targets

In this paper, we consider the problem of tracking multiple maneuvering targets using switching multiple target motion models. With this paper, we aim to contribute in solving the problem of model-based body motion estimation by using data coming from visual sensors. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets whose state and/or measurement (assumed to be linear) models changes during motion transition. However, when these models are nonlinear, the IMM algorithm must be modified in order to guarantee an accurate track. In this paper we propose to avoid the Extended Kalman filter because of its limitations and substitute it with the Unscented Kalman filter which seems to be more efficient especially according to the simulation results obtained with the nonlinear IMM algorithm (IMMUKF). To resolve the problem of data association, the JPDA approach is combined with the IMM-UKF algorithm, the derived algorithm is noted JPDA-IMM-UKF.

Energy-Efficient Sensing Concept for a Micromachined Yaw Rate Sensor

The need for micromechanical inertial sensors is increasing in future electronic stability control (ESC) and other positioning, navigation and guidance systems. Due to the rising density of sensors in automotive and consumer devices the goal is not only to get high performance, robustness and smaller package sizes, but also to optimize the energy management of the overall sensor system. This paper presents an evaluation concept for a surface micromachined yaw rate sensor. Within this evaluation concept an energy-efficient operation of the drive mode of the yaw rate sensor is enabled. The presented system concept can be realized within a power management subsystem.

A Fiber Optic Interferometric Sensor for Dynamic Measurement

An optical fiber Fabry-Perot interferometer (FFPI) is proposed and demonstrated for dynamic measurements in a mechanical vibrating target. A polishing metal with a low reflectance value adhered to a mechanical vibrator was excited via a function generator at various excitation frequencies. Output interference fringes were generated by modulating the reference and sensing signal at the output arm. A fringe-counting technique was used for interpreting the displacement information on the dedicated computer. The fiber interferometer has been found the capability of the displacement measurements of 1.28 μm – 96.01 μm. A commercial displacement sensor was employed as a reference sensor for investigating the measurement errors from the fiber sensor. A maximum percentage measurement error of approximately 1.59 % was obtained.

Automation of the Maritime UAV Command, Control, Navigation Operations, Simulated in Real-Time Using Kinect Sensor: A Feasibility Study

This paper describes the process used in the automation of the Maritime UAV commands using the Kinect sensor. The AR Drone is a Quadrocopter manufactured by Parrot [1] to be controlled using the Apple operating systems such as iPhones and Ipads. However, this project uses the Microsoft Kinect SDK and Microsoft Visual Studio C# (C sharp) software, which are compatible with Windows Operating System for the automation of the navigation and control of the AR drone. The navigation and control software for the Quadrocopter runs on a windows 7 computer. The project is divided into two sections; the Quadrocopter control system and the Kinect sensor control system. The Kinect sensor is connected to the computer using a USB cable from which commands can be sent to and from the Kinect sensors. The AR drone has Wi-Fi capabilities from which it can be connected to the computer to enable transfer of commands to and from the Quadrocopter. The project was implemented in C#, a programming language that is commonly used in the automation systems. The language was chosen because there are more libraries already established in C# for both the AR drone and the Kinect sensor. The study will contribute toward research in automation of systems using the Quadrocopter and the Kinect sensor for navigation involving a human operator in the loop. The prototype created has numerous applications among which include the inspection of vessels such as ship, airplanes and areas that are not accessible by human operators.

Application of Robot Formation Scheme for Screening Solar Energy in a Greenhouse

Many agricultural and especially greenhouse applications like plant inspection, data gathering, spraying and selective harvesting could be performed by robots. In this paper multiple nonholonomic robots are used in order to create a desired formation scheme for screening solar energy in a greenhouse through data gathering. The formation consists from a leader and a team member equipped with appropriate sensors. Each robot is dedicated to its mission in the greenhouse that is predefined by the requirements of the application. The feasibility of the proposed application includes experimental results with three unmanned ground vehicles (UGV).

Acoustic Detection of the Red Date Palm Weevil

In this paper, acoustic techniques are used to detect hidden insect infestations of date palm tress (Phoenix dactylifera L.). In particular, we use an acoustic instrument for early discovery of the presence of a destructive insect pest commonly known as the Red Date Palm Weevil (RDPW) and scientifically as Rhynchophorus ferrugineus (Olivier). This type of insect attacks date palm tress and causes irreversible damages at late stages. As a result, the infected trees must be destroyed. Therefore, early presence detection is a major part in controlling the spread and economic damage caused by this type of infestation. Furthermore monitoring and early detection of the disease can asses in taking appropriate measures such as isolating or treating the infected trees. The acoustic system is evaluated in terms of its ability for early discovery of hidden bests inside the tested tree. When signal acquisitions is completed for a number of date palms, a signal processing technique known as time-frequency analysis is evaluated in terms of providing an estimate that can be visually used to recognize the acoustic signature of the RDPW. The testing instrument was tested in the laboratory first then; it was used on suspected or infested tress in the field. The final results indicate that the acoustic monitoring approach along with signal processing techniques are very promising for the early detection of presence of the larva as well as the adult pest in the date palms.

Parametric Analysis in the Electronic Sensor Frequency Adjustment Process

The use of electronic sensors in the electronics industry has become increasingly popular over the past few years, and it has become a high competition product. The frequency adjustment process is regarded as one of the most important process in the electronic sensor manufacturing process. Due to inaccuracies in the frequency adjustment process, up to 80% waste can be caused due to rework processes; therefore, this study aims to provide a preliminary understanding of the role of parameters used in the frequency adjustment process, and also make suggestions in order to further improve performance. Four parameters are considered in this study: air pressure, dispensing time, vacuum force, and the distance between the needle tip and the product. A full factorial design for experiment 2k was considered to determine those parameters that significantly affect the accuracy of the frequency adjustment process, where a deviation in the frequency after adjustment and the target frequency is expected to be 0 kHz. The experiment was conducted on two levels, using two replications and with five center-points added. In total, 37 experiments were carried out. The results reveal that air pressure and dispensing time significantly affect the frequency adjustment process. The mathematical relationship between these two parameters was formulated, and the optimal parameters for air pressure and dispensing time were found to be 0.45 MPa and 458 ms, respectively. The optimal parameters were examined by carrying out a confirmation experiment in which an average deviation of 0.082 kHz was achieved.

Overview of CARDIOSENSOR Project on the Development of a Nanosensor for Assessing the Risk of Cardiovascular Disease

This paper aims at overviewing the topics of a research project (CARDIOSENSOR) on the field of health sciences (biomaterials and biomedical engineering). The project has focused on the development of a nanosensor for the assessment of the risk of cardiovascular diseases by the monitoring of C-reactive protein (CRP), which has been currently considered as the best validated inflammatory biomarker associated to cardiovascular diseases. The project involves tasks such as: 1) the development of sensor devices based on field effect transistors (FET): assembly, optimization and validation; 2) application of sensors to the detection of CRP in standard solutions and comparison with enzyme-linked immunosorbent assay (ELISA); and 3) application of sensors to real samples such as blood and saliva and evaluation of their ability to predict the risk of cardiovascular disease.

Unified Fusion Approach with Application to SLAM

In this paper, we propose the pre-processor based on the Evidence Supporting Measure of Similarity (ESMS) filter and also propose the unified fusion approach (UFA) based on the general fusion machine coupled with ESMS filter, which improve the correctness and precision of information fusion in any fields of application. Here we mainly apply the new approach to Simultaneous Localization And Mapping (SLAM) of Pioneer II mobile robots. A simulation experiment was performed, where an autonomous virtual mobile robot with sonar sensors evolves in a virtual world map with obstacles. By comparing the result of building map according to the general fusion machine (here DSmT-based fusing machine and PCR5-based conflict redistributor considereded) coupling with ESMS filter and without ESMS filter, it shows the benefit of the selection of the sources as a prerequisite for improvement of the information fusion, and also testifies the superiority of the UFA in dealing with SLAM.

A Robust Extrapolation Method for Curtailed Aperture Reconstruction in Acoustic Imaging

Acoustic Imaging based sound localization using microphone array is a challenging task in digital-signal processing. Discrete Fourier transform (DFT) based near-field acoustical holography (NAH) is an important acoustical technique for sound source localization and provide an efficient solution to the ill-posed problem. However, in practice, due to the usage of small curtailed aperture and its consequence of significant spectral leakage, the DFT could not reconstruct the active-region-of-sound (AROS) effectively, especially near the edges of aperture. In this paper, we emphasize the fundamental problems of DFT-based NAH, provide a solution to spectral leakage effect by the extrapolation based on linear predictive coding and 2D Tukey windowing. This approach has been tested to localize the single and multi-point sound sources. We observe that incorporating extrapolation technique increases the spatial resolution, localization accuracy and reduces spectral leakage when small curtail aperture with a lower number of sensors accounts.