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Deep Learning-Based Computer Vision for Robotics
Abstract
Under vision research, processes, and criteria for robotic vision based on multiple stages were set based on prerequisites for robot vision success, need for vision in industries, and advancements in image processing techniques. AI helps robotics by allowing a collaborative robot to accomplish new jobs based on data trends. Deep learning-based artificial vision is used to replicate human vision. Deep learning uses general-purpose learning techniques and convolution neural networks to learn data-driven representations. Deep learning helps vision robots remove overlaps, distortions, and misalignments. Vision control using a recognition algorithm based on vision schemes is highlighted. In this chapter, existing forms of mobile, data acquisition and control, manipulating, and vision-based robotic systems are introduced. Robotics' key focus areas, such as posture estimation, path planning, and mobility based on picture memory and deep learning, enable qualitative topological navigation, localization, and mapping of the environment.
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