title: ÐÐ»Ð³Ð¾ÑÐ¸ÑÐ¼ Ð¾Ð´Ð½Ð¾Ð²ÑÐµÐ¼ÐµÐ½Ð½Ð¾Ð¹ Ð»Ð¾ÐºÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð¸ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ ÐºÐ°ÑÑÑ Ð¼ÐµÑÑÐ½Ð¾ÑÑÐ¸ Ð² ÑÑÐ»Ð¾Ð²Ð¸ÑÑ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¾Ð¹ ÑÑÐµÐ´Ñ ÑÑÐ½ÐºÑÐ¸Ð¾Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Algorithm for simultaneous localization and mapping under conditions of a dynamic functioning environment
Creators: name: ÐÐ°Ð·Ð°ÑÐµÐ², ÐÐ°ÐºÑÐ¸Ð¼
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: slam
Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ°Ñ ÑÑÐµÐ´Ð°
Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½ÑÐ¹ ÑÐ¾Ð±Ð¾Ñ
Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð¼ÐµÑÑÐ½Ð¾ÑÑÐ¸
Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ðµ ÐºÐ°ÑÑÑ
Ð»Ð¾ÐºÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ
dynamic environment
mobile robot
exploration
mapping
localization

description: Â  Â  Â  Â  Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÑ ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ðµ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°ÑÐ¸ Ð¾Ð´Ð½Ð¾Ð²ÑÐµÐ¼ÐµÐ½Ð½Ð¾Ð¹ Ð»Ð¾ÐºÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð¸ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ ÐºÐ°ÑÑÑ Ð¼ÐµÑÑÐ½Ð¾ÑÑÐ¸ Ð² ÑÑÐ»Ð¾Ð²Ð¸ÑÑ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¾Ð¹ ÑÑÐµÐ´Ñ, Ð¼ÐµÑÐ¾Ð´Ð¸ÐºÐ¸ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ð¹. ÐÐ±ÑÐµÐºÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ Ð¿Ð¾Ð´ÑÐ¾Ð´Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² Ðº ÑÐ°Ð±Ð¾ÑÐµ Ð² ÑÑÐ»Ð¾Ð²Ð¸ÑÑ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¾Ð¹ ÑÑÐµÐ´Ñ. Ð ÑÐ¾Ð´Ðµ Ð´Ð°Ð½Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ñ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ: DynaSLAM, SPW RGB-D SLAM, GMC Motion Clustering, Ð±ÑÐ»Ð¾ Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½Ð¾ Ð½ÐµÑÐºÐ¾Ð»ÑÐºÐ¾ Ð²Ð°ÑÐ¸Ð°Ð½ÑÐ¾Ð² ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð´Ð°Ð½Ð½ÑÑ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð² â Ð¿Ð¾ ÑÐ¸Ð¿Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¸Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð² Ð² Ð¿ÑÐ¾ÑÐµÑÑÐµ ÑÐ°Ð±Ð¾ÑÑ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð¿Ð¾ ÑÐ°ÐºÑÑ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ deep-learning ÑÐµÑÐµÐ½Ð¸Ð¹ Ð´Ð»Ñ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¸Ñ Ð¾Ð±ÑÐµÐºÑÐ¾Ð². Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° ÑÐµÑÐµÐ½Ð¸Ð¹, Ð¿Ð¾Ð´ÑÐ¾Ð´ÑÑÐ¸Ñ Ð´Ð»Ñ Ð±Ð¾ÑÑÐ±Ñ Ñ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¸Ð¼Ð¸ Ð¾Ð±ÑÐµÐºÑÐ°Ð¼Ð¸, ÑÐ´ÐµÐ»Ð°Ð½ Ð²ÑÐ±Ð¾Ñ Ð² Ð¿Ð¾Ð»ÑÐ·Ñ ÑÐµÑÐµÐ½Ð¸Ð¹, Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸ Ð´Ð»Ñ ÑÐµÐ¼Ð°Ð½ÑÐ¸ÑÐµÑÐºÐ¾Ð¹ ÑÐµÐ³Ð¼ÐµÐ½ÑÐ°ÑÐ¸Ð¸ ÑÑÐµÐ½Ñ. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð° ÑÐ¸ÑÑÐµÐ¼Ð° Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¾Ð³Ð¾ SLAM, Ð¿ÑÐ¸Ð²ÐµÐ´ÐµÐ½Ð¾ ÑÐµÐ¾ÑÐµÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð¾Ð¿Ð¸ÑÐ°Ð½Ð¸Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð°. ÐÑÐ¾Ð²ÐµÐ´ÐµÐ½Ñ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÑ Ð½Ð°Ð´ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½ÑÐ¼ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð¾Ð¼, ÐµÐ³Ð¾ ÑÑÐ°Ð²Ð½ÐµÐ½Ð¸Ðµ Ñ Ð°Ð½Ð°Ð»Ð¾Ð³Ð°Ð¼Ð¸.
description: Â  Â  The aim of this work is to explore existing solutions for simultaneous localization and mapping (SLAM) in dynamic environments, as well as methodologies for motion segmentation. The research focuses on various approaches to working in dynamic environments employed by different algorithms. Â  Â  The following algorithms were considered in this work: DynaSLAM, SPW RGB-D SLAM, and GMC Motion Clustering. Several classification options for these algorithms were proposed based on the type of dynamic object usage during operation, and the usage of deep learning solutions for dynamic object segmentation. After reviewing solutions suitable for dealing with dynamic objects, the choice was made in favor of solutions that use neural networks for semantic scene segmentation. The dynamic SLAM system was developed, and the theoretical algorithm description was provided. Experiments were conducted on the developed algorithm, and its comparison with analogs was demonstrated.