System Design and Obstacle Avoidance Algorithm Research of Vacuum Cleaning Robot

Li, Guangling; Pan, Yingtian

doi:10.1109/dcabes.2015.50

Cited by 5 publications

(1 citation statement)

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“…In terms of algorithms for dirt detection, histogram and saliency detection based methods have been proposed [8,9]. Other researchers have focused on developing algorithms for cleaning large area with multiple robots [10,11], system design and obstacle avoidance of vacuum cleaning robot [12], algorithms for complete coverage path planning for cleaning task using multiple robots [13], and algorithms for cleaning robot's cognitive abilities [14]. Commercial cleaning robots are also available and widely used [1, 15,16].…”

Section: Related Workmentioning

confidence: 99%

An Efficient Algorithm for Cleaning Robots Using Vision Sensors

Ravankar

Watanabe

et al. 2019

The 6th International Electronic Conference on Sensors and Applications

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In recent years, cleaning robots like Roomba have gained popularity. These cleaning robots have limited battery power, and therefore, efficient cleaning is important. Efforts are being undertaken to improve the efficiency of cleaning robots. Most of the previous works have used on-robot cameras, developed dirt detection sensors which are mounted on the cleaning robot, or built a map of the environment to clean periodically. However, a critical limitation of all the previous works is that robots cannot know if the floor is clean or not unless they actually visit that place. Hence, timely information is not available if the room needs to be cleaned. To overcome such limitations, we propose a novel approach that uses external cameras, which can communicate with the robots. The external cameras are fixed in the room and detect if the floor is untidy or not through image processing. The external camera detects if the floor is untidy, along with the exact areas, and coordinates of the portions of the floor that must be cleaned. This information is communicated to the cleaning robot through a wireless network. Thus, cleaning robots have access to a `bird’s-eye view’ of the environment for efficient cleaning. In this paper, we demonstrate the dirt detection using external camera and communication with robot in actual scenarios.

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