Design framework for general purpose object recognition on a robotic platform

The advancement in the broader field of Computer Vision is consequential, through past few decades. Therefore, a considerable improvement in object detection and tagging using convolutional neural networks has given way to accurate yet complex methods, which can identify objects in real-time. However, the growth in the area of implementing the algorithms on low powered portable devices has been relatively slow. This paper aims to converge the fields of computer vision and robotics, focusing on implementation of image description applications on an embedded system platform. We aim to integrate Neural Network powered object recognition system ‘YOLO v2’ with a robotic platform to explore the potential applications in the advancing domain of service and personal robotics.