title: Ð ÐµÑÐµÐ½Ð¸Ðµ Ð¿ÑÐ¾Ð±Ð»ÐµÐ¼Ñ Ð»Ð¾ÐºÐ°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð¼Ð¸Ð½Ð¸Ð¼ÑÐ¼Ð° Ð² Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ðµ Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð¿ÑÑÐ¸ Ð¼ÐµÑÐ¾Ð´Ð¾Ð¼ Ð¿Ð¾ÑÐµÐ½ÑÐ¸Ð°Ð»ÑÐ½ÑÑ Ð¿Ð¾Ð»ÐµÐ¹
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: Developing an algorithm that solves the problem of local minima in path planning using the potential field method
Creators: name: Ð§ÐµÐ±Ð¾ÑÐ°ÑÐµÐ²Ð°, ÐÐ°Ð»ÐµÑÐ¸Ñ
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¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ðµ Ð¿Ð¾ÑÐµÐ½ÑÐ¸Ð°Ð»ÑÐ½Ð¾Ðµ Ð¿Ð¾Ð»Ðµ
Ð»Ð¾ÐºÐ°Ð»ÑÐ½ÑÐ¹ Ð¼Ð¸Ð½Ð¸Ð¼ÑÐ¼
Ð³ÑÐ°Ð´Ð¸ÐµÐ½ÑÐ½ÑÐ¹ ÑÐ¿ÑÑÐº
Ð»Ð¾ÐºÐ°Ð»ÑÐ½Ð°Ñ ÑÐµÐ»Ñ
Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¿ÑÑÐ¸
Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½ÑÐ¹ ÑÐ¾Ð±Ð¾Ñ
artificial potential field
local minimum
gradient descent
local goal
path planning
mobile robot

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description: The objective of this research is to develop an algorithm that solves the problem of local minima in path planning using the potential field method. One of the tasks in autonomous robot navigation is to reach a desired position while avoiding obstacles in the environment. Often, it is required for the robot to find the shortest path. In some cases, the robot has complete knowledge of the operating environment and can plan its movement based on an existing map. However, in most cases, the robot only has knowledge of the goal and must reach it using its sensors. This study examines the method of artificial potential field, which offers a good path search speed and computational complexity, suitable for application on both pre-known maps and in real-time scenarios. However, the use of this method can lead to the robot getting stuck in a local minimum. This work investigates the problem of local minima and existing methods to solve it. It presents the implementation of custom methods and compares them with existing ones.