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Mobile robot intelligent path planning method

A mobile robot and path planning technology, applied in the direction of instruments, non-electric variable control, vehicle position/route/height control, etc., can solve problems such as optimization failure, local optimal oscillation of artificial potential field method, etc.

Active Publication Date: 2021-04-09
SHANGHAI INST OF TECH
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In the actual environment, unknown dynamic obstacles may randomly appear. The common methods for dynamic environments include artificial potential field method and dynamic window method. Because the artificial potential field method is easy to fall into the local optimum and oscillate, the problem of optimization failure

Method used

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Embodiment Construction

[0060] The technical solutions in the embodiments of the present invention will be clearly and completely described and discussed below in conjunction with the accompanying drawings of the present invention. Obviously, what is described here is only a part of the examples of the present invention, not all examples. Based on the present invention All other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0061] Such as Figure 1-5 As shown, this embodiment discloses a mobile robot intelligent path planning method, including the following steps:

[0062] Step 1: Create a grid map based on the known static two-dimensional space, set the grid serial number, and select the starting point S and the target point E;

[0063] Step 2: improve the ant colony algorithm for global path planning;

[0064] Step 3: The mobile robot drives on the globally planned path, the sensor module of the m...

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Abstract

The invention discloses an intelligent path planning method for a mobile robot, and the method comprises the steps: building a static two-dimensional grid map, and carrying out the global path planning through an improved ant colony algorithm; enabling the mobile robot sensor module to detect unknown obstacle information, calculating an obstacle motion trail and a robot motion trail, adopts an optimized dynamic window method to carry out local dynamic obstacle avoidance, and taking the current position of the robot as a starting point and a closest key node on a global planning path as a temporary target point to carry out dynamic obstacle avoidance; and enabling the robot to travel along the planned path and safely reach the destination. According to the method, the actual problems of static obstacles and dynamic obstacles in the map environment are comprehensively considered, the heuristic function of the ant colony algorithm is improved, pheromone updating rules are adjusted for global path planning, the optimized dynamic window method is adopted for obstacle avoidance when the robot encounters the dynamic obstacles in the running process, and local path planning is completed; and the robot has higher practicability and research value in actual map operation.

Description

technical field [0001] The invention relates to the field of robot path planning, in particular to an intelligent path planning method for a mobile robot. Background technique [0002] There are two types of obstacles in the map environment where the robot actually operates, one is known static obstacles, and the other is unknown obstacles that appear randomly. Global path planning refers to selecting a path from the starting point to the goal point under the given environmental obstacle conditions, so that the robot can pass through all obstacles safely and without collision. This method of autonomously avoiding obstacles and completing tasks is an important content in the research and application of robots. [0003] For the map of static obstacles, common robot global path planning methods include A* algorithm, Dijkstra algorithm, genetic algorithm, particle swarm algorithm and ant colony algorithm. Among them, the A* algorithm and the Dijkstra algorithm have lower compl...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02G01C21/20
CPCG05D1/0214G01C21/20
Inventor 张谦马向华狄逸群
Owner SHANGHAI INST OF TECH
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