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Abstract
This paper proposes a visual dirt detection algorithm and a novel adaptive tiling-based selective dirt area coverage scheme for reconfigurable morphology robot. The visual dirt detection technique utilizes a three-layer filtering framework which includes a periodic pattern detection filter, edge detection, and noise filtering to effectively detect and segment out the dirt area from the complex floor backgrounds. Then adaptive tiling-based area coverage scheme has been employed to generate the tetromino morphology to cover the segmented dirt area. The proposed algorithms have been validated in Matlab environment with real captured dirt images and simulated tetrominoes tile set. Experimental results show that the proposed three-stage filtering significantly enhances the dirt detection ratio in the incoming images with complex floors with different backgrounds. Further, the selective dirt area coverage is performed by excluding the already cleaned area from the unclean area on the floor map by incorporating the tiling pattern generated by adaptive tetromino tiling algorithm.
Highlights
In the past decade, mobile robot platforms are playing a vital role in the field of security and surveillance, laboratory assistance, medical robots, and professional cleaning tasks
In order to solve the dirt map-based selective dirt area coverage problem, this paper presents improved visual dirt detection algorithm using a three-stage filtering technique for enhancing the dirt detection ratio and a novel adaptive tiling algorithm for selective dirt area coverage
We presented a selective dirt area coverage scheme for reconfigurable morphology based on visual dirt detection technique and polyominoes tiling theory
Summary
Mobile robot platforms are playing a vital role in the field of security and surveillance, laboratory assistance, medical robots, and professional cleaning tasks. Hess et al proposed poisson-driven dirt maps based selective area coverage for floor cleaning robot where random walk pattern is employed to cover the randomly located dirt cells [3]. These motion patterns are ideal for covering the blank surface and cannot fit to cover the complex floors with an arbitrary shape having sharp corners and narrow spaces [16, 17].
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