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

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.

Micro robot as the feature of robotic in healthcare approach from design to application: the State of art and challenges

“…Magnetic control is particularly beneficial when the micro robot needs to be steered with high accuracy to specific locations. However, it requires the micro robot to be within the range of the external magnetic field source, which may limit its mobility and effective range [66]. is advantageous when precise control is not required, and a larger area can be influenced by the acoustic field.…”

“…is advantageous when precise control is not required, and a larger area can be influenced by the acoustic field. However, miniaturization and integration of acoustic control systems can be technically challenging [66].…”

“…It allows for flexible control strategies and facilitates targeted delivery and manipulation at the cellular or molecular level. However, the challenge lies in developing reliable and scalable methods for external control at the nanoscale [66].…”

The Face Detection / Recognition , Perspective and Obstacles In Robotic: A Review

“…Compared to Local Binary Patterns, Haar has higher accuracy. In testing, the Local Binary Pattern Histogram face recognition has a 93% accuracy rate with a confidence level of 2 to 5 [23]. Also, it is possible to identify persons and recognize faces, dynamic and static objects, environments, and custom items by using the Object Recognition and Classification (ORC) method.…”

Integrating Virtual Reality and Robotic Operation System (ROS) for AGV Navigation

“…As the complexity of robotic tasks increases, the number of tests and validations required to ensure performance increases exponentially [14]. This presents a significant issue, as robots are expensive, and hiring someone to work with them is even costlier [15]. Finding an available space to set up a test environment is also potentially expensive and time-consuming.…”