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Distance map reconstruction and jump point path planning method based on anti-collision radius

A path planning and map reconstruction technology, applied in navigation computing tools and other directions, can solve problems such as robustness and real-time performance that cannot meet requirements, redundant detection, and small proportion of obstacles

Active Publication Date: 2020-10-27
NAT UNIV OF DEFENSE TECH
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AI Technical Summary

Problems solved by technology

However, the existing DM generation algorithm does not consider the anti-collision radius of the planning subject when updating, and the update process will always cover the largest area that the wavefront can govern, which is when the proportion of obstacles is small and the spatial distribution of obstacles is sparse. In the large terrain space, it leads to unacceptable computing overhead, and for the non-collision path planning task that meets a certain anti-collision radius, this DM update method has a large number of redundant detections, which is the reason for the robustness of DM in practical applications. and real-time performance cannot meet the requirements in a specific task space

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  • Distance map reconstruction and jump point path planning method based on anti-collision radius

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Embodiment Construction

[0049] Figure 6 to Figure 10 Shows a specific embodiment of a distance map reconstruction and jump point path planning method based on collision avoidance radius of the present invention, including

[0050] Step 1: Construct and initialize a distance map DM based on the collision avoidance radius on the two-dimensional plane eight-connected grid path planning map where the planning subject is located. The data structure of the distance map DM includes the eight-connected path planning map. The obstacle position matrix obst and the distance matrix dist of the same dimension of the grid path planning map, the element obst in the obstacle position matrix obst s Stored are the coordinates of grid n where the obstacle closest to grid s is located, and the element dist in the distance matrix dist s What is stored is the Euclidean distance between grid s and grid n where the nearest obstacle is located;

[0051] In this embodiment, the distance map DM can be used to help the planning sub...

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Abstract

The invention discloses a distance map reconstruction and jump point path planning method based on an anti-collision radius. The method comprises the steps of constructing a distance map based on theanti-collision radius on a two-dimensional plane eight-connected grid path planning map, and initializing the distance map,taking the distance matrix of the distance map as a search space for carryingout path planning on the planning main body, and dynamically updating the distance map according to the wave front of the grid state change when the grid state in the search space changes,and carrying out collision detection according to the obstacle distance information borne by the distance map and the anti-collision radius of the planning main body when a jump point search algorithm is used for carrying out grid expansion and jump point identification in a search space. The method is used for solving the problems of computing resource consumption caused by excessive updating of a redundantarea, low task map dynamic reconstruction and path planning efficiency in a DM fusion process caused by JPS method self planning and the like, and realizing efficient dynamic reconstruction of a taskmap and improving the path planning efficiency.

Description

Technical field [0001] The invention belongs to the field of artificial intelligence technology, and in particular relates to a distance map reconstruction and jump point path planning method based on collision avoidance radius. Background technique [0002] In the field of artificial intelligence, robotics and computer game intelligence are regarded as a comprehensive field that models human perception, planning, decision-making and action capabilities in complex environments. In recent years, various types of robots have been widely used in production and life, and the academic and industrial circles have gradually increased the importance of computer game intelligence. Typical examples include the StarCraft game AI developed by the DeepMind team and the Dota game AI developed by OpenAI. As the basis of all aspects of technology for robots and game non-player characters (NPC, Non-Player Characters), the shortest path planning technology based on uniform grids (uniform grids) ma...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 秦龙唐见兵杨妹尹全军张琪曾俊杰曾云秀谢旭王鹏
Owner NAT UNIV OF DEFENSE TECH
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