title: ÐÐ»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ ÑÐ¾Ð±Ð¾ÑÐ° Ð² ÑÐ¾ÑÐ¸Ð°Ð»ÑÐ½Ð¾Ð¹ ÑÑÐµÐ´Ðµ Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸ÐµÐ¼ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Motion Planning for a Mobile Robot in a Social Environment with Reinforcement Learning
Creators: name: ÐÐ°ÑÐ¸Ð¾Ð½Ð¾Ð², ÐÐ½ÑÐ¾Ð½
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: Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ðµ
Ð°Ð²ÑÐ¾Ð½Ð¾Ð¼Ð½Ð°Ñ Ð½Ð°Ð²Ð¸Ð³Ð°ÑÐ¸Ñ
Ð¿ÑÐµÐ´Ð¾ÑÐ²ÑÐ°ÑÐµÐ½Ð¸Ðµ ÑÑÐ¾Ð»ÐºÐ½Ð¾Ð²ÐµÐ½Ð¸Ð¹
Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ°Ñ ÑÑÐµÐ´Ð°
ÑÐ¾ÑÐ¸Ð°Ð»ÑÐ½Ð°Ñ ÑÑÐµÐ´Ð°
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼
Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½ÑÐ¹ ÑÐ¾Ð±Ð¾Ñ
motion planning
autonomous navigation
collision avoidance
dynamic environment
social environment
machine learning
reinforcement learning
mobile robot

description: ÐÐ±ÑÐµÐºÑÐ¾Ð¼ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÑÑÑÑ Ð¼ÐµÑÐ¾Ð´Ñ Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ ÑÐ¾Ð±Ð¾ÑÐ° Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼ Ð½Ð° Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ ÑÐ¾Ð±Ð¾ÑÐµ Ð² ÑÑÐµÑÐ¼ÐµÑÐ½Ð¾Ð¹ ÑÑÐµÐ´Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ. Ð ÑÐ°Ð±Ð¾ÑÐµ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð¾ ÑÑÑÑÐ¾Ð¹ÑÑÐ²Ð¾ ÑÐ¾Ð²ÑÐµÐ¼ÐµÐ½Ð½Ð¾Ð¹ ÑÐ¸ÑÑÐµÐ¼Ñ Ð½Ð°Ð²Ð¸Ð³Ð°ÑÐ¸Ð¸. ÐÐ¾ÐºÐ°Ð·Ð°Ð½Ð¾, ÑÑÐ¾ Ð¿ÑÐ¸Ð¼ÐµÐ½ÑÐµÐ¼ÑÐµ ÑÐ½Ð¸Ð²ÐµÑÑÐ°Ð»ÑÐ½ÑÐµ Ð¼ÐµÑÐ¾Ð´Ñ Ð½Ðµ ÑÐ¿Ð¾ÑÐ¾Ð±Ð½Ñ Ð¾Ð±ÐµÑÐ¿ÐµÑÐ¸ÑÑ Ð½Ð°Ð´ÐµÐ¶Ð½Ð¾Ðµ Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð² ÑÐ»Ð°Ð±Ð¾ ÑÐ¾ÑÐ¼Ð°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð½ÑÑ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¸Ñ ÑÑÐµÐ´Ð°Ñ, ÑÐ°ÐºÐ¸Ñ ÐºÐ°Ðº ÑÐºÐ¾Ð¿Ð»ÐµÐ½Ð¸Ñ Ð»ÑÐ´ÐµÐ¹. ÐÐ° Ð¾ÑÐ½Ð¾Ð²Ð°Ð½Ð¸Ð¸ Ð°Ð½Ð°Ð»Ð¸ÑÐ¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð¾Ð±Ð·Ð¾ÑÐ° Ð¿ÑÐµÐ´Ð¼ÐµÑÐ½Ð¾Ð¹ Ð¾Ð±Ð»Ð°ÑÑÐ¸ ÑÐ´ÐµÐ»Ð°Ð½ Ð²ÑÐ²Ð¾Ð´ Ð¾ Ð¿ÐµÑÑÐ¿ÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ñ Ð¿Ð¾Ð´ÐºÑÐµÐ¿Ð»ÐµÐ½Ð¸ÐµÐ¼ Ð¸ Ð¾Ð±Ð¾ÑÐ½Ð¾Ð²Ð°Ð½ Ð²ÑÐ±Ð¾Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð´Ð»Ñ Ð´Ð°Ð»ÑÐ½ÐµÐ¹ÑÐµÐ³Ð¾ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ. ÐÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð°Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð²ÑÐ¿Ð¾Ð»Ð½ÐµÐ½Ð° Ð² Ð²Ð¸Ð´Ðµ ÐºÐ¾Ð¼Ð¿Ð¾Ð½ÐµÐ½ÑÐ° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð¹ Ð¿Ð»Ð°ÑÑÐ¾ÑÐ¼Ñ Robot Operating System 2. ÐÐ»Ñ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¸Ñ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð°ÐºÑÑÐ°Ð»ÑÐ½Ð¾Ð¹ ÑÐ¾Ð±Ð¾ÑÐ¾ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¾Ð¹ Ð¿Ð»Ð°ÑÑÐ¾ÑÐ¼Ñ Ð¸ Ð¼Ð¾Ð´ÐµÐ»Ñ ÑÐ¾ÑÐ¸Ð°Ð»ÑÐ½Ð¾Ð¹ ÑÑÐµÐ´Ñ Ð´Ð»Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ñ Ð² ÑÑÐµÑÐ¼ÐµÑÐ½Ð¾Ð¹ ÑÑÐµÐ´Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Gazebo. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÑÐºÑÐ¿ÐµÑÐ¸Ð¼ÐµÐ½ÑÐ¾Ð² Ð¿Ð¾ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°ÑÐ¸ Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ Ð² ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ ÑÑÐµÐ½Ð°ÑÐ¸ÑÑ Ð¿ÑÐ¾Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÐ¾Ð²Ð°Ð»Ð¸ Ð²Ð¾Ð·Ð¼Ð¾Ð¶Ð½Ð¾ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð¹ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð² ÑÐ¸ÑÑÐµÐ¼Ðµ ÑÐ¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ ÑÐ¾Ð±Ð¾ÑÐ°.
description: The object of the study is the motion planning methods of a mobile robot using machine learning. The purpose of the work is to research a motion planning algorithm based on reinforcement learning on a mobile robot model in a three dimensional modeling environment. The paper considers the design of a modern navigation system. It is shown that the applied general-purpose methods are not able to provide reliable planning in poorly formalized dynamic environments, such as clusters of people. Based on an analytical review of the subject area, a conclusion is made about the prospects of methods based on reinforcement learning and the choice of an algorithm for further research is substantiated. The software implementation of the algorithm is made in the form of a component for the Robot Operating System 2 software platform. To perform an experimental study, a model of an actual robotic platform and a model of a social environment for use in the Gazebo three dimensional modeling environment have been developed. The results of experiments on solving the problem of motion planning in various scenarios demonstrated the applicability of the software implementation in the control system of a mobile robot.