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Robot dynamic obstacle avoidance method based on artificial potential field and rolling window

A rolling window and artificial potential field technology, which is applied in the direction of instruments, navigation calculation tools, non-electric variable control, etc., can solve the problem of unsatisfactory global optimization results and achieve the effect of improving optimality

Active Publication Date: 2018-11-06
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

If this method is applied in a complex and wide environment, the global optimization results obtained will be very unsatisfactory.

Method used

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  • Robot dynamic obstacle avoidance method based on artificial potential field and rolling window
  • Robot dynamic obstacle avoidance method based on artificial potential field and rolling window
  • Robot dynamic obstacle avoidance method based on artificial potential field and rolling window

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Embodiment Construction

[0042] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0043] Such as figure 1 As shown, before step S1, we need to construct and store the static map feature information of the environment into the mobile robot.

[0044] S1: Input parameters, that is, the absolute safety distance D between the mobile robot and the obstacle and the coordinate information X(x, y) of the navigation target point in the constructed map.

[0045] S2: According to the historical data of the robot's odometer, that is, the odometer data at the time of ∞ → 0, and then combined with the environmental feature information E scanned by the laser sensor at this time 0i (i=1,2,...,n) is matched with the map environment model to locate the current pose of the robot

[0046] by E ti (i=1,2,...,n) and It can be judged that the global coordinates of obstacles in the environment at time t are O oti (X ti ,Y ti ):

[0047]...

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Abstract

The invention relates to a robot dynamic obstacle avoidance method based on an artificial potential field and a rolling window, and belongs to the technical field of robot path planning. The method comprises the following steps: S1, setting the absolute safety distance D of a moving robot to an obstacle and the position coordinate information X(x, y) of a destination; S2, determining the pose X0 of the current robot in a global coordinate system according to the historical odometer data of the robot and the current environmental information E0i; S3, initially planning an optimal path Sfirst under a current window by using an A-star path finding algorithm and starting to execution; S4, scanning and updating the real-time environment information E1i under the current window by using a rolling window method, and calculating whether there is an obstacle in the environment within the [delta]t time window; S5, determining whether the distance to the obstacle is within the set absolute safetydistance; and S6, determining whether the robot reaches the coordinate position X (x, y) of the destination, and ending the navigation if so. The method of the invention effectively improves the optimality of the dynamic global path planning.

Description

technical field [0001] The invention belongs to the technical field of robot path planning, and relates to a dynamic obstacle avoidance method for a robot based on an artificial potential field and a rolling window. 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. There are many better solutions to avoid obstacles safely and effectively and reach the destination accurately in a known static environment. However, when the obstacles in the environment are moving, and the position and speed of the obstacles are changing all the time, the real-time and accuracy of the obstacle avoidance algorithm in the robot's navigation process are higher than those in the static environment. Higher, if you continue to use the algorithm in the...

Claims

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Application Information

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IPC IPC(8): G05D1/02G01C21/20
CPCG01C21/20G05D1/024
Inventor 魏新周详宇张毅王斌方继康
Owner CHONGQING UNIV OF POSTS & TELECOMM
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