Computer Vision Based Pick and Place Robotic Arm

Kruna Rathod

ISBN 10: 6209662242 / ISBN 13: 9786209662249

Published by LAP LAMBERT Academic Publishing, 2026

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Computer vision plays a vital role in enhancing the capabilities of robotic arms by enabling them to perceive and understand their surroundings. It involves the use of cameras, sensors, and advanced image processing algorithms to capture and analyze visual data from the environment. This allows robotic systems to perform tasks with a higher level of intelligence, precision, and adaptability.The working process of computer vision in a robotic arm begins with image acquisition, where a camera captures real-time images or video of the workspace. These images are then processed using various techniques such as filtering, edge detection, segmentation, and feature extraction. The system identifies important characteristics like shape, size, color, and texture of objects. Machine learning and deep learning algorithms are often used to recognize and classify objects based on trained datasets.Once the object is identified, the system determines its position and orientation in space, often referred to as localization. This information is crucial for guiding the robotic arm to interact with the object accurately.

Seller Inventory # 9786209662249

Bibliographic Details

• Title: Computer Vision Based Pick and Place Robotic Arm
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2026
• Language: English
• ISBN 10: 6209662242
• ISBN 13: 9786209662249
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 4D millimeters 220 millimeters width by 150 millimeters height by 4 millimeters depth
• Weight: 113 grams

About this title

Synopsis

Computer vision plays a vital role in enhancing the capabilities of robotic arms by enabling them to perceive and understand their surroundings. It involves the use of cameras, sensors, and advanced image processing algorithms to capture and analyze visual data from the environment. This allows robotic systems to perform tasks with a higher level of intelligence, precision, and adaptability.The working process of computer vision in a robotic arm begins with image acquisition, where a camera captures real-time images or video of the workspace. These images are then processed using various techniques such as filtering, edge detection, segmentation, and feature extraction. The system identifies important characteristics like shape, size, color, and texture of objects. Machine learning and deep learning algorithms are often used to recognize and classify objects based on trained datasets.Once the object is identified, the system determines its position and orientation in space, often referred to as localization. This information is crucial for guiding the robotic arm to interact with the object accurately.