Abstract
Most cleaning robots have a good cleaning performance for small environments such as houses but require a longer cleaning time due to problems such as slow cleaning progress and low battery capacity, making the robots unsuitable for large environments such as libraries and airports. Cleaning large environments with multiple robots is faster than cleaning them with a single robot. Multi-cleaning robots can utilize several robots to simultaneously clean and share the task of cleaning among the robots. However, as the number of robots increases and the effective distribution of cleaning is not efficient during the cleaning process, the cleaning time will consequently be longer due to the frequent collisions between the robots. Therefore, to shorten the cleaning time, multi-cleaning robots require a coverage path planning that uses an effective cleaning distribution method in the cleaning process. In this paper, a coverage path planning using a cleaning distribution method based on map decomposition is proposed to reduce the cleaning time of multi-cleaning robots. The experimental results demonstrated that the proposed multi-cleaning robots' coverage path planning could be used in large environments in the presence of several types of obstacles. Furthermore, the cleaning time was found to be shorter than that of the previous methods in the case of multi-cleaning robots.
Highlights
Multi-cleaning robots have become an important research topic in the field of cleaning robots [1]
The cleaning robot used in the experiment was the kobuki robot1 developed by Yujin Robotics (Korea)
In this paper, we proposed an multi-cleaning robots’ coverage path planning (MRCPP) method that could be applied in unknown large environments
Summary
Multi-cleaning robots have become an important research topic in the field of cleaning robots [1]. Multi-cleaning robots are more robust [4], energy efficient [5], and demonstrate a superior spatial distribution [6]. In a sizeable environment, the cleaning time is shorter when multiple robots are used [4]. If the number of robots increases but the cleaning coordination does not perform effectively during the cleaning process, the cleaning time will be longer due to the frequent collisions between the robots [7]. To shorten the cleaning time, we described a multi-cleaning robots’ coverage path planning (MRCPP) method using a cleaning distribution method for multi-cleaning robots. The MRCPP method calculates a path that can cover all the cleanable space while coordinating the multiple robots with a cleaning distribution method in a known or an unknown environment [8]
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