Perception is related to many robotic applications where sensory data and artificial intelligence techniques are involved. The goal of perception is to sense the dynamic environment surrounding the robot and to build a reliable and detailed representation of this environment based on sensory data. Since all subsequent localization, planning, and control depends on correct perception output, its significance cannot be overstated. Perception modules usually include stereo matching, object detection, scene understanding, semantic classification, etc. The recent developments in machine learning, especially deep learning, have exposed robotic perception systems to more tasks, which have been discussed in the last chapter. In this chapter, we will focus on the algorithms and FPGA implementations in the stereo vision system, which is one of the key components in the robotic perception stage.
Perception on FPGAs — Stereo Vision
2021-01-01
18 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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|Cyclopean stereo vision for depth perception [1915-13]
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