DeltaCharger: Charging Robot with Inverted Delta Mechanism and CNN-driven High Fidelity Tactile Perception for Precise 3D Positioning

التفاصيل البيبلوغرافية
العنوان: DeltaCharger: Charging Robot with Inverted Delta Mechanism and CNN-driven High Fidelity Tactile Perception for Precise 3D Positioning
المؤلفون: Okunevich, Iaroslav, Trinitatova, Daria, Kopanev, Pavel, Tsetserukou, Dzmitry
سنة النشر: 2021
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Robotics, Computer Science - Machine Learning
الوصف: DeltaCharger is a novel charging robot with an Inverted Delta structure for 3D positioning of electrodes to achieve robust and safe transferring energy between two mobile robots. The embedded high-fidelity tactile sensors allow to estimate the angular, vertical and horizontal misalignments between electrodes on the charger mechanism and electrodes on the target robot using pressure data on the contact surfaces. This is crucial for preventing a short circuit. In this paper, the mechanism of the developed prototype and evaluation study of different machine learning models for misalignment prediction are presented. The experimental results showed that the proposed system can measure the angle, vertical and horizontal values of misalignment from pressure data with an accuracy of 95.46%, 98.2%, and 86.9%, respectively, using a Convolutional Neural Network (CNN). DeltaCharger can potentially bring a new level of charging systems and improve the prevalence of mobile autonomous robots.
Comment: Accepted to IEEE Robotics and Automation Letters and 17th International Conference on Automation Science and Engineering (CASE) 2021, IEEE copyright, 7 pages, 9 figures
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2107.10710
رقم الأكسشن: edsarx.2107.10710
قاعدة البيانات: arXiv