The problem at solving which the project is aimed consists in the development of methods of constructing a threedimensional combined dense map are of the accessible environment and determining a position of a robot in a relative coordinate system based on a history of camera positions and the robot's motions, symbolic (semantic) tags.
In the present work new methods and algorithms for selecting features using deep learning techniques based on autoencoders will be proposed to provide high informativeness with low within-class and high between-class variance. The performance of the proposed methods in real indoor environments is presented and discussed.
The present work will propose a new heuristic algorithms for path planning of a mobile robot in an unknown dynamic space that have theoretically approved estimates of computational complexity and are approbated for solving specific applied problems.
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