Abstract
Abstract: Grasping unstructured objects with a robotic manipulator is a difficult task. The challenge lies in both determining which objects are desirable to grasp and where those objects are relative to the manipulator. However, a robotic arm with an eye-in-hand camera can be used to effectively grab and hold desired objects, even if the exact geometry and position of the objects are unknown before the experiment. Combining Convolutional Neural Networks in image processing and Monoscopic Depth Analysis for visual-servoing, it was successfully demonstrated that a robotic manipulator could be used to accurately locate and grasp a leaf from a plant while only using a single camera for identification. This task of finding and manipulating a leaf shows the potential of using robotic manipulators in increasingly unstructured environments.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
