Browsing by Author "Harshanath, S.M.B."

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Computer Vision Based Navigation Robot
(IEEE, 2022-12-26) Haputhanthri, M; Himasha, C; Balasooriya, H; Herath, M; Rajapaksha, S; Harshanath, S.M.B.
The majority of industrial environments and homewares need help when exploring unknown locations owing to a lack of understanding about the building structure and the various impediments that may be faced while transporting products from one spot to another. This is because there is a lack of knowledge about the building structure and the potential obstacles that may be encountered. This paper provides “Computer Vision-Based Navigation Robot” as a strategy for indoor navigation with optimal accessibility, usability, and security, decreasing issues that the user may encounter when traveling through indoor and outdoor areas with real-time monitoring of the most up to date IoT technology. The article is titled “Indoor Navigation with Optimal Accessibility, Usability, and Security.” This article proposes “Computer Vision-Based Navigation Robot” as a solution for interior navigation that provides optimum accessibility, usability, and security. This is done in order to tackle the issue that was presented before. Since the readers of this post include people who work in industry as well as physically challenged people who live alone, CVBN Robot takes object-based inputs from its surroundings. This is because the audience for this essay includes both groups of people. This study also covers a variety of methods for localization, sensors for the detection of obstacles, and a protocol for an Internet of Things connection between the server and the robot. This connection enables real-time position and status updates for the robot as it navigates a known but unknown interior environment. In addition, this study covers a variety of methods for localization, sensors for the detection of obstacles, and a protocol for an Internet of Things connection between the server and the robot.
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EasyTalk: A Translator for Sri Lankan Sign Language using Machine Learning and Artificial Intelligence
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Kumar, D.M.; Bavanraj, K.; Thavananthan, S.; Bastiansz, G.M.A.S.; Harshanath, S.M.B.; Alosious, J.
Sign language is used by the hearing-impaired and inarticulate community to communicate with each other. But not all Sri Lankans are aware of the sign language or verbal languages and a translation is required. The Sri Lankan Sign Language is tightly bound to the hearing-impaired and inarticulate. The paper presents EasyTalk, a sign language translator which can translate Sri Lankan Sign Language into text and audio formats as well as translate verbal language into Sri Lankan Sign Language which would benefit them to express their ideas. This is handled in four separate components. The first component, Hand Gesture Detector captures hand signs using pre-trained models. Image Classifier component classifies and translates the detected hand signs. The Text and Voice Generator component produces a text or an audio formatted output for identified hand signs. Finally, Text to Sign Converter works on converting an entered English text back into the sign language based animated images. By using these techniques, EasyTalk can detect, translate and produce relevant outputs with superior accuracy. This can result in effective and efficient communication between the community with differently-abled people and the community with normal people.
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Learning Assistant To Acquire The Fundamental Language Skills for Non-Native Learners Using AI
(2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Srikanthan, P.; Nizar, R.; Ravikumar, A.; Lalitharan, K.; Harshanath, S.M.B.; Alosius, J.
The ability to speak and learn a language properly requires good practice, experience and good learning strategies but the existing solutions do not provide proper guidance to learn a language with instant feedback. This research is an approach to devise an improved language learning assistant with practices that will help to improve the fundamental language skills for non-native learners and children who are in the early stage of their education. The four main skills focused on this application will be conversation, pronunciation, listening and grammatical skills. The implementation of this research is done by using technologies like natural language processing, machine learning, and deep learning approaches to come up with components to train the learner. The solution of this research is delivered by using a cross-platform application called GLIB which facilities to improve all the English language skills mentioned above along with guides, tips, practices, and feedback based on an evaluation to improve the English language.
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Plant Suggestion and Monitoring Robot
(IEEE, 2022-12-09) Karunarathna, R.M.N.P; Senadeera, T D D; Sumesh Ranka, M B; Gunasinghe, D V R; Rajapaksha, U.U.S; Harshanath, S.M.B.
The goal of all agricultural production is to produce goods economically and efficiently while using the fewest resources possible. Nonetheless, agriculture’s return on investment has been steadily declining. This study combines several approaches in the form of a multipurpose robot to improve the precision of agricultural decision-making. Four novel features of the robot are revealed. An advanced autonomous navigation system based on the well-established Turtle-bot architecture, innovative environmental monitoring, and analysis tool for detecting any unexpected changes in the environment, and An environmental and soil monitoring and visualization tool would be used to maintain equal strands throughout the entire cultivation area. A program that monitors the land’s environmental and soil conditions and generates intelligent crop recommendations for the initial phase of cultivation. The robot as a whole is designed to support cultivation from the starting phase to well-established cultivation in an efficient manner.
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Train a Robot to Climb Staircase Using Vision-Base System
(Institute of Electrical and Electronics Engineers, 2022-09-16) Jayawardana, J.T.H.; Dilshan, H.V.V; Wijethilaka, R.G.K.H; Balasooriya, T.D; Rajapaksha, U.U.S; Harshanath, S.M.B.; Jayawardena, C
Currently, robots are used for different types of work, such as the manufacturing industry, healthcare, and the hotel industry. According to the current epidemic situation, the usage of robots was increased because of the need to reduce human interaction. As a result, they have to walk around the workplace, because of that, they may have to climb staircases. The world has many types of robots. Here the selected robot is a humanoid. This proposal is concerned with how to detect the staircase, count steps, get dimensions of it, and move the robot on it by keeping body balance. First, want to know what the objects are, then walk. The identified images from the image sensors will get as input. The technology stack that is used for image analysis is a method related to computer vision in deep learning. Other than that, while climbing the stairs robot needs to identify whether the staircase is over or not. Here we introduce a new concept: get the number of steps required to climb before climbing the stairs. It is related to how humans identify things by seeing and making decisions. The need to take the dimensions of the stairs is that when considering the stairs, they have their height, width, and range. Therefore, it is imperative to calculate the dimensions of each staircase separately. Creating a balance system similar to human balance is a great advantage in robotics. To implement such a system, there is an upright pose controller to allow the robot to walk stably by preventing tilting of the robot during walking on uneven floor. In general, for us to do that we need to calculate the global inclination of the floor is a key factor. It can be measured with a 2-axis accelerator meter, and it is installed in the inertial sensor.