Path planning method based on simulated plant growth guided RRT algorithm

A technology for path planning and plant growth, which is applied in the direction of navigation calculation tools, etc., can solve the problems of low operation efficiency of RRT algorithm, achieve the effects of improving execution efficiency and stability, improving executable performance, and improving tracking effect

Active Publication Date: 2018-10-16
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem of low operational efficiency of the current RRT algorithm in comp

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  • Path planning method based on simulated plant growth guided RRT algorithm
  • Path planning method based on simulated plant growth guided RRT algorithm
  • Path planning method based on simulated plant growth guided RRT algorithm

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Embodiment Construction

[0042] The present invention will be further described below in conjunction with accompanying drawing:

[0043] Such as Figure 1~3 As shown, a path planning method based on the simulated plant growth guided RRT algorithm includes the following steps:

[0044] Step 1: Initialize the map information: import the map and rasterize the map, import the boundary and obstruction (roadblock) information and binarize the map information, initialize the coordinates of the starting point and target point, the array of path points, and set the starting point as the current point (x, y), the target point is the light source point (Goal x, Goal y ), the growth step;

[0045] Step 2: Calculate the influence of growth and obstruction of roadblocks in all directions at the current point;

[0046] Step 3: Determine whether the light source point can be seen directly, if yes, output the path point array, and execute step 11;

[0047] Step 4: Calculate the gravitational force of light on the...

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Abstract

The invention discloses a path planning method based on a simulated plant growth guiding RRT (rapidly-exploring random tree) algorithm. The method comprises the following steps: initializing map information; calculating the roadblock blocking influences on the growth at a current point in every direction; judging whether a light source point can be directly seen or not; calculating the light attraction borne by the current point; calculating the resultant force borne by the current point; calculating the current growth direction of terminal buds, and growing a step length unit; judging whetherthe coordinates of a new position are outside a boundary or within the roadblock or not; updating the current point to be a new position, and storing the new position as a path point array; judging whether the current point is a target point or not; outputting the path point array; planning a path through the RRT algorithm; judging whether a new path can be found or not; and carrying out cubic Bezier curve fitting. The algorithm provided by the invention greatly improves the tracking effect of the RRT algorithm, and the sampling of the traditional RRT algorithm is random sampling, so tree nodes generated by the improved algorithm cover the entire map area with the rising of the number of iterations.

Description

technical field [0001] The invention relates to the field of path intelligent planning, and more specifically, relates to a path planning method based on a simulated plant growth guiding RRT algorithm. Background technique [0002] The problem of path planning has always been a research hotspot in the field of intelligent robots. Path planning for mobile robots means that the robot plans a non-collision, safe and feasible path from the starting point to the end point based on the environmental information obtained by the airborne sensors, and on this basis, as far as possible Optimize paths where possible. [0003] Path planning algorithms have been widely studied in the field of mobile robots, and many classic path planning algorithms have been proposed, mainly including artificial potential field method, visual graph method, mathematical programming method and so on. The artificial potential field method has good real-time performance and is easy to implement, but it is e...

Claims

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Application Information

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IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 计时鸣郗枫飞温聪蔡超鹏何瑛俏
Owner ZHEJIANG UNIV OF TECH
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