Journal
2021 26TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA)
Volume -, Issue -, Pages -Publisher
IEEE
DOI: 10.1109/ETFA45728.2021.9613366
Keywords
Autonomous mobile robots; computer vision; intelligent sensors and actuators; deep learning methods; factory automation
Categories
Funding
- RFBR [20-38-90294]
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MobileCharger is a novel mobile charging robot that utilises advanced technologies for electrode detection and precise positioning, with high performance and efficiency demonstrated in experiments.
MobileCharger is a novel mobile charging robot with an Inverted Delta actuator for safe and robust energy transfer between two mobile robots. The RGB-D camera-based computer vision system allows to detect the electrodes on the target mobile robot using a convolutional neural network (CNN). The embedded high-fidelity tactile sensors are applied to estimate the misalignment between the electrodes on the charger mechanism and the electrodes on the main robot using CNN based on pressure data on the contact surfaces. Thus, the developed vision-tactile perception system allows precise positioning of the end effector of the actuator and ensures a reliable connection between the electrodes of the two robots. The experimental results showed high average precision (84.2%) for electrode detection using CNN. The percentage of successful trials of the CNN-based electrode search algorithm reached 83% and the average execution time accounted for 60 s. MobileCharger could introduce a new level of charging systems and increase the prevalence of autonomous mobile robots.
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