Multifunctional Robot Using Computer by Ranganathan Arivazhagan (10 results)

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Taschenbuch. Condition: Neu. MULTIFUNCTIONAL ROBOT USING COMPUTER VISION | COMPUTER VISION | Arivazhagan Ranganathan (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208440091 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The Book titled 'Multi Functional Robot Using Computer Vision' presents the development of an advanced robotic system designed to perform tasks such as object detection, recognition, and manipulation using computer vision. The robot, built by a team of Mechatronics Engineering students, integrates hardware components like the Raspberry Pi 4, L298N motor drivers, servo motors, and mecanum wheels for omnidirectional movement. Powered by Python-based algorithms, OpenCV, and ROS (Robot Operating System), the robot employs YOLOv3 for real-time object detection and ORB-SLAM for navigation and mapping. The 5-degree-of-freedom robotic arm enables precise object manipulation, while torque and power calculations ensure optimal performance. Testing demonstrated an 80% success rate in grasping and less than 5% error in navigation. The project highlights the potential of computer vision in robotics, with future enhancements including 3D reconstruction, machine learning integration, and a user-friendly GUI. This work contributes to the advancement of autonomous robotic systems for industrial and logistical applications. 60 pp. Englisch.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The Book titled 'Multi Functional Robot Using Computer Vision' presents the development of an advanced robotic system designed to perform tasks such as object detection, recognition, and manipulation using computer vision. The robot, built by a team of Mechatronics Engineering students, integrates hardware components like the Raspberry Pi 4, L298N motor drivers, servo motors, and mecanum wheels for omnidirectional movement. Powered by Python-based algorithms, OpenCV, and ROS (Robot Operating System), the robot employs YOLOv3 for real-time object detection and ORB-SLAM for navigation and mapping. The 5-degree-of-freedom robotic arm enables precise object manipulation, while torque and power calculations ensure optimal performance. Testing demonstrated an 80% success rate in grasping and less than 5% error in navigation. The project highlights the potential of computer vision in robotics, with future enhancements including 3D reconstruction, machine learning integration, and a user-friendly GUI. This work contributes to the advancement of autonomous robotic systems for industrial and logistical applications.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The Book titled 'Multi Functional Robot Using Computer Vision' presents the development of an advanced robotic system designed to perform tasks such as object detection, recognition, and manipulation using computer vision. The robot, built by a team of Mechatronics Engineering students, integrates hardware components like the Raspberry Pi 4, L298N motor drivers, servo motors, and mecanum wheels for omnidirectional movement. Powered by Python-based algorithms, OpenCV, and ROS (Robot Operating System), the robot employs YOLOv3 for real-time object detection and ORB-SLAM for navigation and mapping. The 5-degree-of-freedom robotic arm enables precise object manipulation, while torque and power calculations ensure optimal performance. Testing demonstrated an 80% success rate in grasping and less than 5% error in navigation. The project highlights the potential of computer vision in robotics, with future enhancements including 3D reconstruction, machine learning integration, and a user-friendly GUI. This work contributes to the advancement of autonomous robotic systems for industrial and logistical applications.