airo 22(1): e13

Research Article

The Object Detection, Perspective and Obstacles In Robotic: A Review

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  • @ARTICLE{10.4108/airo.v1i1.2709,
        author={Ge  Xu and Amir Sohail Khan and Ata Jahangir Moshayedi and Xiaohong  Zhang and Yang Shuxin},
        title={The Object Detection, Perspective and Obstacles In Robotic: A Review},
        journal={EAI Endorsed Transactions on AI and Robotics},
        volume={1},
        number={1},
        publisher={EAI},
        journal_a={AIRO},
        year={2022},
        month={10},
        keywords={Deep Learning, Object Detection, Image Processing, Salient Object Detection (SOD), 3D object detection},
        doi={10.4108/airo.v1i1.2709}
    }
    
  • Ge Xu
    Amir Sohail Khan
    Ata Jahangir Moshayedi
    Xiaohong Zhang
    Yang Shuxin
    Year: 2022
    The Object Detection, Perspective and Obstacles In Robotic: A Review
    AIRO
    EAI
    DOI: 10.4108/airo.v1i1.2709
Ge Xu1, Amir Sohail Khan1, Ata Jahangir Moshayedi1,*, Xiaohong Zhang1, Yang Shuxin1
  • 1: Jiangxi University of Science and Technology
*Contact email: moshaydi@gmail.com

Abstract

A few years back, when the image processing hardware and software were created, it was limited, and most of the time, object detection would fail., But as with time, the advancement in technology has significantly changed the scenario. A lot of researchers worked in this field to carry out a solution through which they can detect objects in any field, especially in the robotic domain [1]. In today's world, with so much research in the field of deep learning, it is very easy to identify and detect any object using computer vision. This paper focuses on the various deep learning technologies and algorithms through which object detection can be done. A new and advanced deep learning technology known as salient object detection has been discussed. Also, the 3D object detection and the end-to-end approach for object detection are discussed. The existing methods of deep learning through which object detection can be done. The applications in which object detection is being used and the importance of object detection. It also reports; what the predecessors have done, what problems have been solved by them, how they solved these problems, the characteristics of the predecessors' methods and their future work.