Mobile robot multi-resolution full coverage path planning algorithm

The mobile robot can independently run the core as SLAM and path planning [1]. In the grid method drawing, high-precision positioning requires a high-resolution grid. When a mobile robot covers a certain working area, since the coverage width is constant each time, when high-efficiency coverage is required, a low-resolution grid is required for path planning, and a multi-resolution raster problem occurs. For the full coverage path planning problem of multi-resolution mobile robots, this paper proposes the use of high-precision grid positioning, low-resolution raster path planning coverage. In the normal grid traversal process, this paper adopts a mobile robot full coverage path planning algorithm based on bio-excitation network, which can be autonomous exploration traversal. This paper actually models its algorithm, and increases direction guidance and robot into dead zone. When escaping from the dead zone as soon as possible according to greedy thoughts, the algorithm has good real-time performance, can automatically avoid obstacles and escape from the dead zone, and there will be no large-scale folding back. Especially in the field of cleaning, the follow-on mobile robot can effectively clean the narrow area. It can make the cleaning car recycle garbage and has high cleaning efficiency. In the process of high resolution to low resolution, there are both moving obstacles and movable motion grids. This paper uses quadtree segmentation and Hilbert curve to traverse the motion grid to improve coverage and efficiency. The edge of the rule explores the purpose of reciprocating the entire region by reciprocating the unknown environment. In the experiment, it is proved that the algorithm of this paper has higher coverage efficiency by comparing with the original biological excitation network algorithm.