AI Article Synopsis
- The cleaning robot is the most popular type of service robot, and this paper introduces an efficient recharging mechanism for when its battery is low.
- The mechanism uses a combination of motor encoders and neural networks to accurately determine the robot's position and a self-rotating camera to locate the docking station through infrared detection.
- By integrating six-axis acceleration and ultrasound technology, the system effectively corrects for navigation errors caused by collisions, leading to improved recharging efficiency.
Article Abstract
Cleaning robot has the highest penetration rate among the service robots. This paper proposes a high-efficiency mechanism for an intelligent cleaning robot automatically returns to charging in a short time when the power is insufficient. The proposed mechanism initially combines the robot's own motor encoder with neural network linear regression to calculate the moving distance and rotation angle for the location estimation of the robot itself. At the same time, a self-rotating camera is applied to scan the number of infrared spots on the docking station to find the location of the docking station so that the cleaning robot returns to charging properly in two stages, existing infrared range and extended infrared range. In addition, six-axis acceleration and ultrasound are both applied to deal with the angle error that is caused by collision. Experimental results show that the proposed recharging mechanism significantly improves the efficiency of recharging.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263651 | PMC |
| http://dx.doi.org/10.3390/s18113911 | DOI Listing |
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