Browsing by Author "Kahatapitiya, N. S"

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Open Access
Electromagnetic Continuously Variable Transmission (EMCVT) System for Precision Torque Control in Human-Centered Robotic Applications
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-09-08) Madusankha, I; Jayaweera, P. N; Kahatapitiya, N. S; Sampath, P; Weeraratne, A; Subasinghage, K; Liyanage, C; Wijethunge, A; Ravichandran, N. K; Wijesinghe, R. E
In human-centered robotic applications, safety, efficiency, and adaptability are critical for enabling effective interaction and performance. Incorporating electromagnetic continuously variable transmission (EM-CVT) systems into robotic designs enhances both safety and precise, adaptable motion control. The flexible power transmission offered by CVTs allows robots to operate across diverse environments, supporting various tasks, human interaction, and safe collaboration. This study presents a CVT-based mechanical subsystem developed using two cones and an intermediate belt-driven transmission mechanism, providing efficient power and motion transfer. The control subsystem consists of six strategically positioned electromagnets energized by signals from a microcontroller. This electromagnetic actuation enables rapid and precise adjustments to the transmission ratio, enhancing overall system performance. A linear relationship between slip percentage and gear ratio was observed, indicating that the control system achieves stable and efficient operation, with a measured power consumption of 2.95 W per electromagnet. Future work will focus on validating slip performance under dynamic loading conditions, integrating the system into robotic platforms, and optimizing materials and control strategies to enable broader real-world deployment.
Embargo
Environmental forensics of the X-press pearl disaster: Uncovering the internal micro-structural transformations in marine microplastics
(Elsevier B.V., 2025-07-15) Jayasekara, P.M; Abhishek, P; Kahatapitiya, N. S; Weerasinghe, M; Kahandawala, B. S; Silva, B. N; Wijenayake, U; Rajapaksha, A.U; Wijesinghe, R. E; Vithanage, M
The MV X-Press Pearl (XPP) maritime disaster on May 25, 2021, released approximately 75 billion microplastic (MP) nurdles into the Indian Ocean and degraded due to the elevated temperatures, a cocktail of chemicals, physical abrasions, and environmental factors. While degradation-induced surface-level chemical and morphological changes were well documented, internal degradation remains largely unexplored. This study highlights the utilization of high-resolution optical coherence tomography (OCT) as a purely non-destructive imaging modality to discover profound internal alterations in the micrometer range, such as internal hollow regions, cracks, and voids in MP nurdles subjected to different degrees of degradation. The dark pixel intensity probability density corresponds to the degraded areas, increased from 0.0019 (pristine nurdle) to 0.0135–0.5252 for thermal degradation, 0.0878–0.3134 for chemical degradation, and 0.1291–0.2179 for mechanical degradation, indicating progressive internal degradation. Attenuated total reflectance fourier transform infrared (ATR-FTIR) spectroscopy analysis confirmed that all the nurdles are polyethylene (PE) and revealed that extreme conditions lead to the formation of new functional groups, including hydroxyl bands and carbonyl bands, even though PE is highly resistant to degradation. The integration of high-resolution OCT imaging with FTIR analysis provides novel insights into the interconnection between micrometer-scale internal physical alterations and associated chemical modifications of MP nurdles resulting from environmental degradation. These findings highlight the potential of this OCT-FTIR integrated approach for advancing the understanding of MP degradation and its long-term environmental impacts.
Open Access
Optical Coherence Imaging Hybridized Deep Learning Framework for Automated Plant Bud Classification in Emasculation Processes: A Pilot Study
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-09-25) Tharaka, D; Withanage, A; Kahatapitiya, N. S; Abhayapala, R; Wijenayake, U; Wijethunge, A; Ravichandran, N. K; Silva, B. N; Jeon, M; Kim, J
A vision-based autonomous system for emasculating okra enhances agriculture by enabling precise flower bud identification, overcoming the labor-intensive, error-prone challenges of traditional manual methods with improved accuracy and efficiency. This study presents a framework for an adaptive, automated bud identification method to assist the emasculation process, hybridized optical coherence tomography (OCT). Three YOLOv8 variants were evaluated for accuracy, detection speed, and frame rate to identify the most efficient model. To strengthen the findings, YOLO was hybridized with OCT, enabling non-invasive sub-surface verification and precise quantification of the emasculated depth of both sepal and petal layers of the flower bud. To establish a solid benchmark, gold standard color histograms and a digital imaging-based method under optimal lighting conditions with confidence scoring were also employed. The results demonstrated that the proposed method significantly outperformed these conventional frameworks, providing superior accuracy and layer differentiation during emasculation. Hence, the developed YOLOv8 hybridized OCT method for flower bud identification and emasculation offers a powerful tool to significantly improve both the precision and efficiency of crop breeding practices. This framework sets the stage for implementing scalable, artificial intelligence (AI)-driven strategies that can modernize and optimize traditional crop breeding workflows.
Open Access
Real-Time Coordinate Estimation for SCARA Robots in PCB Repair Using Vision and Laser Triangulation
(Multidisciplinary Digital Publishing Institute (MDPI), 2025-04-07) Sanjeewa, N; Wathudura, V. M; Kahatapitiya, N. S; Silva, B. N; Subasinghage, K.; Wijesinghe, R.E
The Printed Circuit Board (PCB) manufacturing industry is a rapidly expanding sector, fueled by advanced technologies and precision-oriented production processes. The placement of Surface-Mount Device (SMD) components in PCB assembly is efficiently automated using robots and design software-generated coordinate files; however, the PCB repair process remains significantly more complex and challenging. Repairing faulty PCBs, particularly replacing defective SMD components, requires high precision and significant manual expertise, making automated solutions both rare and difficult to implement. This study introduces a novel real-time machine vision-based coordinate estimation system designed for estimating the coordinates of SMD components during soldering or desoldering tasks. The system was specifically designed for Selective Compliance Articulated Robot Arm (SCARA) robots to overcome the challenges of repairing miniature PCB components. The proposed system integrates Image-Based Visual Servoing (IBVS) for precise X and Y coordinate estimation and a simplified laser triangulation method for Z-axis depth estimation. The system demonstrated accuracy rates of 98% for X and Y axes and 99% for the Z axis, coupled with high operational speed. The developed solution highlights the potential for automating PCB repair processes by enabling SCARA robots to execute precise picking and placement tasks. When equipped with a hot-air gun as the end-effector, the system could enable automated soldering and desoldering, effectively replacing faulty SMD components without human intervention. This advancement has the potential to bridge a critical gap in the PCB repair industry, improving efficiency and reducing dependence on manual expertise.