Mobile robot path planning method based on improved RRT algorithm

A mobile robot, path planning technology, applied in instruments, motor vehicles, non-electric variable control, etc., can solve the problems of low planning success rate, non-optimal path, poor real-time performance of RRT* algorithm, etc.

Active Publication Date: 2020-09-01
SHENYANG LIGONG UNIV
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Problems solved by technology

[0004] In view of the non-optimal path of the RRT algorithm, the low success rate of planning in complex environments, and the poor real-time performance of the RRT* algorithm, the present invention proposes a mobile robot path planning method based on the improved RRT algorithm to overcome the above-mentioned prior art improve the success rate and real-time performance of the algorithm in complex environments, reduce the randomness of the path, and make the planned path as close to the optimal as possible

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  • Mobile robot path planning method based on improved RRT algorithm
  • Mobile robot path planning method based on improved RRT algorithm
  • Mobile robot path planning method based on improved RRT algorithm

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[0062] The invention will be further described below in conjunction with the accompanying drawings and specific implementation examples.

[0063] like figure 1 As shown, a mobile robot path planning method based on the improved RRT algorithm includes the following steps:

[0064] Step 1: Collect the working environment information of the robot through the visual camera, lidar sensor, ultrasonic sensor, and infrared sensor equipped with the mobile robot, and then use information fusion and SLAM (Simultaneous Localization And Mapping for short SLAM) technology to establish a map of the working environment of the mobile robot. Among them, the visual camera collects the image information of the obstacle, the laser radar sensor and the ultrasonic sensor collect the position information of the surrounding objects, and the infrared sensor collects the distance information between the mobile robot and the obstacle. Figure 4 ~ Figure 6 In , the black part is the obstacle area, and th...

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Abstract

The invention provides a mobile robot path planning method based on an improved RRT algorithm in an indoor environment. A high-precision grid map of a robot working environment is established; map segmentation is carried out, and then a next grid needing to be searched is determined by adopting a neighborhood extension strategy; the type of a search grid and the number of effective sampling pointsare determined through a random sampling experiment, then the effective sampling points are added into a random tree according to a neighborhood optimal principle, state updating is conducted on thegrid based on a memory strategy, and finally smoothing processing is conducted on an obtained planning path through a pruning algorithm and a Bezier curve. Due to introduction of map segmentation andobstacle edge detection ideas, the sampling efficiency of an RRT algorithm in complex maps such as narrow channels is improved; due to introduction of a memory mechanism and a neighborhood extension strategy, the planning success rate of the algorithm in a complex environment is increased; a father node is selected according to the neighborhood optimal mode, and problems that the algorithm randomness is high, and the path is not optimal are solved.

Description

technical field [0001] The invention relates to the technical field of mobile robot path planning, in particular to a mobile robot path planning method based on an improved RRT algorithm. Background technique [0002] With the development and progress of science and technology, intelligent robots are more and more widely used in human life. As a key technology of intelligent robots, path planning is the basis for performing various advanced tasks and realizing autonomous navigation. Its purpose is to find a collision-free path from the starting point to the target point in an environment with obstacles. At present, the commonly used path planning algorithms mainly include rapidly expanding random tree (RRT), random road map method (PRM), A-star, Dijkstra (Dijkstra), artificial potential field, fuzzy logic algorithm, particle swarm algorithm, ant group algorithm, etc. Among them, the A-star and Dijkstra algorithms are not suitable for large-scale or high-precision grid maps...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/0242G05D1/0246G05D1/0255G05D1/0257G05D2201/0217Y02T10/40
Inventor 蒋强易春林冯永新隋涛
Owner SHENYANG LIGONG UNIV
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