Browsing by Author "Mark, R.A.D.R.K."

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    Autonomous Lawn Mower
    (Uva Wellassa University of Sri Lanka, 2019) Mark, R.A.D.R.K.; Amarasinghe, A.R.P.C.C.J.
    Modern houses include a compound often used as garden with grass which grows and need to be maintained at a short height. Conventional lawn mowing is often a hassle and time consuming in cutting the grass. The task of manual lawn mowing can be replaced by autonomous lawn mower using a robot programmed to perform such task. A robotic lawn mower is designed and installed in this research, So the main research problem is creating an Automatic lawn mower that will allow house owners to maintain their lawn without spending much time and money, with the specialties of autonomous robot can mow the lawn of a given specific area of the garden without any human supervision, easy and simple preparation and the robot must be affordable cost for local market. For the implement part of the research following materials and soft wares used RF receiver and transmitter, Lipo- Polymer battery, Grass cutting blade and motor, Arduino Mega 2560 development board used DC gear motors with encoders and MPU6050 gyroscope was used for localization part and for the programming IDE Arduino 1.8.2 was used.
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    Computerized Motor Spare Parts Identifier
    (Uva Wellassa University of Sri Lanka, 2018) Mark, R.A.D.R.K.; Wickrama, M.L.
    The use of image processing for physical characteristics identifier for auto spare parts selling industry systems was the aim of this research. Furthermore, this research is to develop an identifier of physical properties, which are altered in used spare parts and identify the correct spare part that should be used to replace. In Sri Lankan scenario, a replacement of a spare part is done by hand measurements and selection through manuals. An automated system could reduce time consumed in this process. The images were taken from the USB2.0 HD UVC WebCam and the images were processed using MATLAB R2016a software. Arduino Mega 2560 development board was used to control the hardware. Moreover, the system is programmed to check the availability of the spare parts through the already established data base. MySQL database managing software is used to develop the database manipulation. Presently, the system can identify oil seals. Further a robotic arm and Auto Guided Vehicle to deliver the suitable part to the consumer via the fully automated process is expected to develop. Keywords: Image processing, Spare part identifier, Automated system
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    Development a Self-Driving Golf Cart Using Kinect Sensor and Robot Operating System (ROS)
    (Uva Wellassa University of Sri Lanka, 2021) Thilakarathna, M.M.R.U.; Bandara, T.U.K.S.; Ekanayake, R.M.T.C.B.; Mark, R.A.D.R.K.; Gunasekara, L.K.I.K.
    An automated guided vehicle (AGV), in general, follows markings or wires on the floor or uses vision or laser sensors for its navigation. AGVs have been applied for flexible manufacturing systems, storage systems, delivery systems and in many similar situations in the industry mainly to move materials around a manufacturing facility or a warehouse. They are programmable mobile vehicles. AGVs are advantageous over conventional material transportation methods because its repeatability and economic savings because of the absence of labor. The aim of this paper is to develop an automated golf cart for human transportation. To date, in Sri Lanka, there is no self- driving system for human transportation. Hence, by introducing an electrical self-driving solution for the Sri Lankan transportation system, environmental impacts and exhaust emissions can be reduced which are generated by fossil fuel consumption. The price of petrol is increasing due to shortage in supplying crude oil. If there is an electric self-driving system, the shortage of fuel can be overcome. This AGV system can be used in large factories, hotels, gardens and parks for human transportation. This self-driving technology may create new industries and job opportunities for thousands of employees in Sri Lanka. Paper presents an autonomous navigation AGV system based on a Robot Operating System (ROS) for indoor and outdoor navigation tasks. This system uses a Kinect sensor for map building of its environment. First, the system was developed and simulated using the ROS platform. Then, this self-navigation system was applied to a real golf cart by updating its control and drive system to match with the new self-navigation system. In this update, the Ackerman steering system and the braking system of the golf cart was automated to work in parallel with the new controller. This innovative system can carry up to four persons at a time. Experimental trials showed the ability of the AGV to move loads and people to their target locations. Keywords: AGV; ROS; Kinect Sensor; Ackerman Steering System; Automated Navigation
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    Self-Navigated Vehicle for Industrial Applications
    (Uva Wellassa University of Sri Lanka, 2019) Kumara, I.D.D.; Mark, R.A.D.R.K.; Amarasinghe, A.R.P.C.C.J.
    This study presents the innovation of the industrial autonomous navigation system. AVG installation consist of several building components; the vehicle, safety system, battery charging system, communication system, navigation system, traffic management system, job control system and other external components. Each of these systems has provided a specific function. Specially navigation system has provided the ability for the vehicle to identify its position. AGVs have to make decisions on path selection. The sensors installed on its on-board computer possessed all the data to calculate the position and orientation of the AGV. Sensors also capable of detecting magnetic markers made of tape of opposite polarity. Every AGV has a mapping system and a copy of the route map stored in its onboard computer. The route map contains routes, obstacles and pick up and drop up points. The encoders mounted on each wheel of AGV able to measure the steering angle and count the number of wheel revolution. Usually magnetic tape used as a path selection technique in AGVs. Here the position is identified using IMU (Inertial measurement unit) module. In here Euler angels were used to find the direction. Conventionally IMU module produces enormous noise and not enough accurate to use in specific applications. But in this study, the noise of IMU module is decreased and the accuracy is increased by the Kalman filter and the algorithm was built by us. The main purpose of this research is to make a more reliable automated industrial vehicle which can use and install easily. The sticking problems and maintaining difficulties are avoided. This modified AGVs have a high degree of flexibility to transfer material to the destined position. They only recharge when there is a gap in their auto planning and their recharge is a dynamic process. AGV provide an accurate and predictable material delivery, handling loads at different heights, complete routines, flexibility, clear aisles and organized workstations (Grid navigation) and its safe for people and loads.