A sweeping robot cleaning path planning and navigation control method

Abstract

The invention discloses a cleaning path planning and navigation control method for a sweeping robot, which belongs to the field of robots. The method uses a gyroscope and a code disc to estimate the current pose of the robot, combines cleaning line planning, and uses along-line motion control and edge-side motion control, so that The sweeping robot completes high-efficiency bow-shaped cleaning in a closed indoor space, and does not need to be equipped with a map storage unit, which greatly reduces the production cost of the robot. It has low cost, minimal dependence on memory, and fast computing speed. It can run at 600 frames per second in the STM32F0x0 chip with the lowest cost of STM chips. It can run immediately after booting, and adapt to different environments during cleaning. Coverage efficiency and coverage rate Much higher than the random collision type, the route navigation method greatly reduces the collision between the machine, the wall and the furniture, and reduces the damage to the environment and the product itself. The linear walking accuracy is high, and the continuous straight line is 20m, and the deviation from the target line is less than 20mm. Satisfy the cleaning and navigation in the open field.

Description

technical field [0001] The invention relates to the field of robots, in particular to a sweeping robot cleaning path planning and navigation control method. Background technique [0002] The cleaning path planning method currently applied to sweeping robots has the following defects: [0003] (1) High cost. The current technology needs to store the map and consumes a lot of memory. Chips above 512kb must be used, resulting in high cost of computing equipment. [0004] (2) It is necessary to explore the workspace and build a map before starting the cleaning task. It takes a long time to explore when cleaning a large space. [0005] (3) Most of the cleaning planning algorithms currently applied to low-cost chips are random collisions, and the cleaning coverage and coverage efficiency are low, which cannot meet the normal use requirements. [0006] (4) The random collision scheme has low coverage at the edge of the room where a lot of debris is piled up. Contents of the inv...

AI Technical Summary

Problems solved by technology

[0003] (1) High cost. Due to the need to store the map in the current technology, the memory consumption is large, and chips above 512kb must be used, resulting in high cost of computing equipment

[0004] (2) It is necessary to explore the workspace and build a map before starting the cleaning task. It takes a long time to explore when cleaning a large space

[0005] (3) Most of the cleaning planning algorithms currently applied to low-cost chips are random collisions, and the cleaning coverage and coverage efficiency are low, which cannot meet the normal use requirements

[0006] (4) The random collision scheme has low coverage at the edge of the room where a lot of debris is piled up

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