An Optimization Method for Satellite Data Structure Design Based on Improved Ant Colony Algorithm

Zhao, Jincheng; Ye, Mian

doi:10.1109/access.2023.3290174

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…By combining various path planning algorithms with environmental maps, we can achieve path planning for mobile robots. Since ant colony algorithms have highly efficient searchability [22][23][24][25][26][27], it has also become a commonly used path planning method. This paper proposed a method to transform the non-standard real environment map into the standard robot mobile environment map-occupancy grid map, and to then use ant colony optimization algorithms to realize the robot moving path, position, and pose planning.…”

Section: Introductionmentioning

confidence: 99%

Non-Standard Map Robot Path Planning Approach Based on Ant Colony Algorithms

Li,

Kim,

2023

Sensors

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Robot path planning is an important component of ensuring the robots complete work tasks effectively. Nowadays, most maps used for robot path planning obtain relevant coordinate information through sensor measurement, establish a map model based on coordinate information, and then carry out path planning for the robot, which is time-consuming and labor-intensive. To solve this problem, a method of robot path planning based on ant colony algorithms after the standardized design of non-standard map grids such as photos was studied. This method combines the robot grid map modeling with image processing, bringing in calibration objects. By converting non-standard actual environment maps into standard grid maps, this method was made suitable for robot motion path planning on non-standard maps of different types and sizes. After obtaining the planned path and pose, the robot motion path planning map under the non-standard map was obtained by combining the planned path and pose with the non-standard real environment map. The experimental results showed that this method has a high adaptability to robot non-standard map motion planning, can realize robot path planning under non-standard real environment maps, and can make the obtained robot motion path display more intuitive and convenient.

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