7-DOF Robotic Manipulator for Autonomous Segregation using Transfer Learning

7 DOF Robotic arm provides an efficient solution for segregating objects using transfer learning a deep-learning method. Segregating objects though may not sound a difficult task, but when automated requires complex detection algorithms and proper set-up. This complex setup is useful when segregating hazardous substances which human hands cannot do. The robotic arm used comprises 7 dynamixels, giving it 7 degrees of freedom (DOF). There are many solutions for this task, but this paper mainly focuses on using a transfer learning technique for detecting objects and then segregating. Transfer learning is used because deep-learning has much more time complexity than transfer learning. Hence this proves to be an efficient method.