Object Detecting Robot Identifying & Picking Up Objects

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dc.contributor.advisorMd. Shahriar Hussain
dc.contributor.authorRaisa Akhtar
dc.contributor.authorZarin Musharrat
dc.contributor.authorAlifa Khan
dc.contributor.id2012010042
dc.contributor.id1931826642
dc.contributor.id1931829642
dc.coverage.departmentElectrical and Computer Engineering
dc.date.accessioned2025-04-28
dc.date.accessioned2025-04-28T05:06:41Z
dc.date.available2025-04-28T05:06:41Z
dc.date.issued2023
dc.description.abstractThis research focuses on the development of an accurate object detection algorithm to aid robots in identifying and picking up objects in cluttered environments. Object detection is crucial for robotic control systems, particularly in industrial automation. Traditional object detection algorithms struggle with objects lacking texture, leading to the adoption of deep learning methods like YOLO (You Only Look Once) for improved performance. The study aims to enhance object localization accuracy, especially in cluttered scenes, to facilitate robot grasping tasks. While basic YOLO models can detect objects, precise localization remains challenging. The research proposes a solution using deep YOLOs for semantic segmentation, which significantly improves object localization accuracy. Despite being time-consuming, YOLOv8 proves highly efficient, achieving an accuracy of 84.7%. The ultimate goal is to implement a robot capable of detecting and identifying five objects (ball, bottle, car, cup, spoon), and then picking and placing them according to user instructions. For the hardware part, we have used the Arduino UNO microcontroller, which is quite budget-friendly. As this is just a small test project, only a robotic arm gripper is used here, so that it can only grab it if it recognizes the object.
dc.description.degreeUndergraduate
dc.identifier.cd600000381
dc.identifier.print-thesisTo be deteremined
dc.identifier.urihttps://repository.northsouth.edu/handle/123456789/1147
dc.language.isoen
dc.publisherNorth South University
dc.rights©Nsulibrary
dc.titleObject Detecting Robot Identifying & Picking Up Objects
dc.typeProject
oaire.citation.endPage38
oaire.citation.startPage1
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