Browsing by Author "Wijesooriya, P.N."

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    Convert 2D Images to 3D Image
    (Uva Wellassa University of Sri Lanka, 2013) Gaspe, G.M.S.M.; Ekanayake, R.M.T.C.B.; Wijesooriya, P.N.
    Image processing plays a major role in modern technology. Implementations of this field are varying from simple applications like documentation to complex applications like space context. Before use in the above applications images should be processed using relevant techniques. There are many software that can process the images and get the outputs to be used in the above mentioned applications. Conversion of 2D images into 3D format is essential in applications such as automatic navigation of robots and vehicles, satellite identification and fault diagnosis, medical reasoning and remote surgery (Pollefeys et al., 2000). With developed software user can obtain 3D images using 2D images in a lesser time and the human interaction have been eliminated to a single step. Methodology MATLAB is a technical computing language used throughout the research (Background on matlab image processing toolboxes, 2013). The system allows user to input two stereo images of the object which is to be converted into 3D. Then the image pair is read and converted to gray scale for the matching process. To have more efficient and accurate results two system objects were used. Basically red-cyan channel images give 3D visualization when visualized with 3D spectacles or one with a red and cyan vision. So the conversion of two stereo images to cyan and red is done. RGB value of cyan is 0,255,255 and RGB value of red is 255, 0, 0. So left image is (:,:,1:1)=0 and right image is(:,:,2:3)=0;. For the best block matching step, extract the 7 X 7 pixel block is considered in the right image and search along the same row in the left image (Image point matching, 2013). Sum of absolute difference is used to compare the image regions. Template Matcher System object is used to increase the accuracy of blocks matching (www.imageprocessingbook.com). Then allocating space for all template matcher system objects is done. Scan is done over all rows and columns and disparity bound is calculated for each. Then template and region of interest is constructed. Depth map have positive values only. Finally As there are noisy patches and bad depth estimates everywhere noise filtration is done.
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    Industrial Ultrasonic Tank Liquid Capacity Indicator
    (Uva Wellassa University of Sri Lanka, 2013) Wattegedara, P.U.; Wijesooriya, P.N.; Ekanayake, R.M.T.C.B.
    Industrial automation is a vast area of research & implemented in different scales. A large number of researchesare conducting throughout the world to find optimum and most cost effective systems. In these researches, instruments measuring liquids and control systems are taken very important place (Mohammad, 2009.). Using this technology it indicates liquid capacity and control liquid automatically. Results two weeks industrial visit and I have seen this issue at Palwatta sugar factory & distillery plant use manual capacity level measuring techniques (Figure 2) or mechanical systems (Figure 1) to measure tanks liquid stock. These manual systems need additional human resources and mechanical systems to overcome the errors due to the friction of pulleys and ropes. Because of these issues inaccurate readings are obtained.
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    Kinect Human Follower
    (Uva Wellassa University of Sri Lanka, 2013) Hansajeewa, K.H.; Ekanayake, R.M.T.C.B.; Wijesooriya, P.N.
    In near future people will need their own personal robot for day to day work. With this trend education, entertainment and security, especially in defense, the market for robots will be enormously high (Saccoccio & Taleb, 2013). The range of the camera in Microsoft's Kinect, intended for the Xbox 360 gaming console, offers a powerful alternative to many standard sensors used in robotics for gathering spatial information about a robot’s surroundings (Schwab, 2011). The recently released Kinect is the first commercially available product which provides the depth data of its resolution and accuracy reach of many robotics projects. This project aims to design and construct a mobile autonomous robot which can navigate independently taking gesture commands from Kinect sensor in a very cost effective way in order to be used in home application (MikkelViager, 2011). Methodology The project is divided into two parts: hardware implementation and software implementation. The platform provides the robot’s mobility and serves as the base of the robot (Schwab, 2011). All of the other components are mounted on the base. The steering consists of two links. One steering link consists of a medium caster wheel and other consisting with two wheels driven by 12 Volt two DC motors. The circuit design consists of microcontrollers circuit with max 232 for serial communication. Motor controlling circuit was constructed using H-Bridge. The system software can be broken down into several components that approximately correspond to the hardware components. OpenNI, NITE from PrimeSense were downloaded and installed.Visual Studio 2008 was installed to further implementation of Kinect sensor. Results and Discussion Overall goal of this project was to identify the commands and Kinect’s ability to provide sufficient sensory information to perform basic navigation. The first program was tested to identify the ability of the device. Therefore invincible pen was created using hand. Procedure was completed successfully to draw lines using invincible pen.The system was tested to identify the depth image. Kinect could able to identify the depth image. Closer objects are dark in color and objects that are further away are lighter in color of the depth image. Figure 1 depicts the Kinect depth data represented as an image.Also of importance, there are noticeable black regions in this image that Kinect can’t identify. To take the gesture command Prime sense NITE should be linked with openNI.Visual studio 2008 unable to link Prime sense NITE with openNI. Therefore the Kinect unable to perform gesture commands. The motors successfully operated for a long time and delivered a better torque to the wheels in order to carry higher weights. Motor controlling of the robot was successfully actuated. The circuit which was prepared for serial communication was successfully operated. It could able to communicate with PC and Microcontroller.
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    Landmine contaminated area scanning robot
    (Uva Wellassa University of Sri Lanka, 2015) Senevirathne, M.M.G.T.L.; Ekanayake, T.; Wijesooriya, P.N.
    Landmines pose serious threats for post conflict countries like Sri Lanka. There are nearly 120 million landmines all over the world today. Unlike other weapons, landmines are long term killers and function long after a war is over. It kills and maims more than 20,000 civilians per year (World Vision. 2009. About Landmines. United States: World Vision). Clearing the burial mines by human is lethal. Though autonomous mine detecting machines are available, the cost is high and one shortage of the systems is not providing a map of the scanned area. Therefore the percent work aim to design a prototype of an economical autonomous robot which facilitates the mine detecting and map generating of buried places. Methodology The black color marks in a white background were considered as landmines and IR sensors were used as detectors. The complete design is consisting of detectors, carrying vehicle and controlling unit. There are three detectors which are placing in three sides of the robot and each detector consists of five IR sensors. The analog signals of the detector were converted in to digital by using the LM 339 comparator. The separate presets were used to adjust the reference voltage with the comparator. The LED bulbs were placed in front of the sensors to avoid the disturbance of infra-red rays of the sunlight. The detector of the moving side was only activated at a time and other two were deactivated in that time. The robot has to scan the total area and the moving pattern of the robot is the most important part and key feature of the design. It moving on straight lines and moving perpendicular direction without turning. The special wheel was used for this function and the wheels have cylindrical rollers to reduce the friction when it is moving in perpendicular direction. The robot is moving by using the two pairs of wheels. The two pairs wheels arranged in perpendicular direction and driven by gear motors. The L 293 motor drivers were used to control the motors. The 12V 6800mAh li-ion rechargeable battery was used as the power supply of the robot and the power transmission was done by using the L7805 regulators. The powers for the motors were supplied through the two 1000 micro farad capacitors. It avoids the restart of the processor because of the over consumption power of the motors. The regulated power was smooth further and given to the processor. All of the operation was processed by the Arduino Mega at mega 2560 microprocessor. The robot is moving 1m front while scanning the area and doing the serial communication. Then stay 1 second for stable the robot and moving 20cm perpendicular direction and after 1 second delay it is moving back. Then again do the perpendicular movement. The serial communication is occurring while these movements. This process is repeating 5 times again and again. The counter was used to control the repeating times of the cycle. The real time data communication was done by serial communication and data received by a serial terminal. The USB port was functioning as the virtual serial port. The communication port and the baud rate should be same. Baud rate can be set as the requirement. The predefined Matlab application generated the map.
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    Mobile Robot using Fuzzy Logic
    (Uva Wellassa University of Sri Lanka, 2013) Fayas, U.L.M.; Ekanayake, R.M.T.C.B.; Wijesooriya, P.N.
    Fuzzy logic controllers have gained popularity in the past few decades with highly successful implementation in many fields. Fuzzy logic enables designers to control complex systems more a low-cost microcontroller-based tool for fuzzy logic controlled, line following mobile robot. educational Traditional methods to control any dynamic system require the use of some knowledge, or model, of the system to be controlled. An accurate model is crucial for the successful implementation of a control algorithm. Unfortunately, most systems in real life are nonlinear, highly complex, and too difficult or impossible to model accurately. Fuzzy logic is a mathematical system which helps to reduce the complexity of controlling nonlinear systems (pierreguillemin, 1996) (vamsimohanperi, 2002) (Nhivekaret et al., 2011). Fuzzy logic expresses operational laws of a control system in linguistic terms instead of the traditionally used mathematical equations. The linguistic terms are most often expressed in the form of logical expressions, such as IF_THEN (Nhivekaret et al., 2011). The line following robot presented here follows a black line drawn over white surface. When the curve path comes ahead the speed is reduced using fuzzy logic control algorithms. The inputs for the robot were obtained from infrared sensors mounted on the robot platform. These inputs were sent to a Microchip PIC16F877 microcontroller on the robot, which analyses the dataand provides the necessary control signal. A fuzzy logic controller is used to control the robot’s motion along the predefined path. The robot algorithm was first done in Matlab and the fuzzy logic rules were optimized for the results possible. Later the microcontroller was programmed in C language using a PIC C-compiler and tested (Nhivekar et al, 2011). Experimental results are presented to show the performance of the controller.
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    Robotic Frog
    (Uva Wellassa University of Sri Lanka, 2013) Wijeratne, Y.M.J.U.; Wijesooriya, P.N.; Ekanayake, R.M.T.C.B.
    All jumping involves the application of force against a substrate, which in turn generates a reactive force that propels the jumper away from the substrate (Willoms, 2006; Armour et al., 2007). Any solid or liquid capable of producing an opposing force can serve as a substrate, including ground or water. Examples of the latter include dolphins performing traveling jumps, and Indian skitter frogs executing standing jumps from water (D.E. Koditschek. and M. Bühler, 1991; Willoms, 2006). There are several types of projects done before in amphibious robotics for imitate animal’s locomotive mechanisms, behaviors in different environments, imitate their sounds (Saito et al., 1994; Willoms, 2006). In this project it is focused to imitate the mechanism of frog which use for their locomotion. Methodology To control the servo in 360 degrees, gears of the servo were modified because in normal conditions, they do not allow more than 180 degrees rotation. Then controlling circuit was prepared to give pulses to the servo for its rotation. Two NES 537 servo motors were used in this project. To modify the gear system, first the potentiometer was removed and a resister unit was added.