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Sensor fusion and improved Q learning algorithm based dynamic barrier avoidance method

A technology of dynamic obstacle avoidance and learning algorithm, which is applied to instruments, surveying and navigation, navigation computing tools, etc., and can solve problems such as small amount of calculation and real-time performance

Active Publication Date: 2019-03-08
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

Each has its own advantages and disadvantages. For example, the artificial potential field method has a small amount of calculation and good real-time performance, but it is prone to local minimum points

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  • Sensor fusion and improved Q learning algorithm based dynamic barrier avoidance method
  • Sensor fusion and improved Q learning algorithm based dynamic barrier avoidance method
  • Sensor fusion and improved Q learning algorithm based dynamic barrier avoidance method

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Embodiment Construction

[0046] The technical solutions in the embodiments of the present invention will be described clearly and in detail below with reference to the drawings in the embodiments of the present invention. The described embodiments are only some of the embodiments of the invention.

[0047] The technical scheme that the present invention solves the problems of the technologies described above is:

[0048] Such as image 3 As shown, the dynamic obstacle avoidance method of mobile robot based on sensor fusion and Q learning algorithm, the method includes the following steps:

[0049] S1: Set the safety distance dm between the robot and the obstacle, and the target coordinate position information (x t ,y t ) and range Rm;

[0050] S2: Determine the current pose of the robot (x r ,y r ,θ r ), and combine the static map information with the target point (x t ,y t ) carry out navigation path planning, and start to move forward;

[0051] S3: During the navigation process, the enviro...

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Abstract

The invention relates to a sensor fusion and improved Q learning algorithm based dynamic barrier avoidance method. The method comprises the steps that S1) the safe distance to a barrier and target coordinate position information and scope during movement of a robot are set; S2) a present pose of the robot is determined, a navigation path is planned, and forwarding is started; S3) in the navigationprocess, environment data detected by a sonar sensor and environment data detected by a laser sensor are preprocessed and characterized and then fused to obtain environment data; S4) whether dynamicbarrier avoidance is needed for the present robot state is determined according to the fused environment data, if YES, a step S5) is carried out, and otherwise, a step S6) is carried out; S5) an improved Q learning dynamic barrier avoidance method is used to obtain the next motion state (a, theta); and S6) whether the robot reaches a target point is determined, if NO, the step S2) is returned to continue navigation, and otherwise, navigation is ended. The method can be used to overcome defects of the single sensor effectively, and improve the barrier avoidance efficiency in the dynamic environment.

Description

technical field [0001] The invention belongs to the technical field of robot path planning, and relates to a dynamic obstacle avoidance method of a mobile robot based on sensor fusion and Q learning algorithm. Background technique [0002] Path planning is one of the key elements of an autonomous mobile robot. It is hoped that the mobile robot can reach the destination as quickly and accurately as possible, and it is also required that the robot can safely and effectively avoid obstacles in the environment. At present, there are many better solutions to safely and effectively avoid obstacles and accurately reach the destination in a static environment. However, when there are moving obstacles in the environment, and the speed and position of the obstacles are changing all the time, the real-time and accuracy of the obstacle avoidance algorithm in the navigation process of the mobile robot are higher than those in the static environment. Higher, if you continue to use the al...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02G01C21/20
CPCG05D1/0231G05D1/0255G01C21/005G01C21/20
Inventor 张毅魏新周详宇李晋宏
Owner CHONGQING UNIV OF POSTS & TELECOMM
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