Enhanced map learning path planning method for indoor mobile robot

A mobile robot and learning path technology, which is applied in the field of indoor mobile robot enhanced map learning path planning, can solve the problems of not being able to satisfy the dynamic environment and real-time performance at the same time, restricting the path selection of indoor mobile robots, and complex planning and decision-making

Active Publication Date: 2015-01-21
HUNAN UNIV
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the changing and complex environment and the need to consider many factors, its planning decisions become very complicated
In the existing technology, conventional path planning, such as fuzzy programming, genetic algorithm, ant colony alg

Method used

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  • Enhanced map learning path planning method for indoor mobile robot
  • Enhanced map learning path planning method for indoor mobile robot
  • Enhanced map learning path planning method for indoor mobile robot

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Embodiment Construction

[0053] The present invention will be further described below in conjunction with the accompanying drawings and specific implementation examples.

[0054] Such as figure 1 As shown, the present invention is an indoor mobile robot enhanced map learning path planning method, including the following steps:

[0055] Step 1: Establish a probability model that the detected area is affected by obstacles;

[0056] Firstly, the surrounding environment information of the indoor mobile robot is obtained through the sonar sensor carried by the indoor mobile robot itself; secondly, the area passed by the indoor mobile robot is regarded as the detected area, and the detected area is established based on the surrounding environment information. The probability model of the impact, and update the probability model of the detected area affected by obstacles in real time according to the surrounding environment information collected by the sonar sensor in real time;

[0057] In the step 1, the...

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Abstract

The invention discloses an enhanced map learning path planning method for an indoor mobile robot. The method includes the steps that (1) ambient environment information is acquired, and an obstacle probability density model is established; (2) path planning is carried out through a greedy algorithm and an enhanced map learning method; (3) path selection and self-adaptation speed strategy adjustment are conducted on the indoor mobile robot. By the adoption of the enhanced map learning path planning method, a current optimal path can be planned in real time according to the current condition of the indoor mobile robot and the inherent non-holonomic constraint of the robot, meanwhile, the obstacle crossing ability, the target point convergence ability and the planning efficiency of the indoor mobile robot can be considered through the self-adaptation speed strategy adjustment, and therefore the indoor mobile robot can arrive at a specific location safely and effectively.

Description

technical field [0001] The invention relates to the field of autonomous navigation of ground wheeled robots, in particular to an enhanced map learning path planning method for indoor mobile robots. Background technique [0002] With the development of robotics and the deepening of artificial intelligence research, intelligent robots are playing an increasingly important role in human life. As a kind of common living robots, indoor mobile robots are mostly used in complex dynamic environments such as indoor mobile exhibitions, home services, and hotel lobby guidance as a substitute for service personnel. In this type of environment, the environmental information is unstructured, static and dynamic obstacles are staggered, and the environmental information changes significantly. These factors pose great challenges and requirements to the working ability of indoor mobile robots. In order to better complete service tasks, indoor mobile robots need to have the ability to detect ...

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Application Information

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IPC IPC(8): G05D1/02G05B13/04
Inventor 王耀南陈彦杰钟杭潘琪
Owner HUNAN UNIV
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