mlsanityData to 14 Oct 2026

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

arXiv 2107.10710 ↗First posted 22 Jul 2021cs.RO cs.LGcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 5 of its 27 references that are in the map. First posted on arXiv 22 Jul 2021.

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5 of 27 references.

References · 5

  1. 2015Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shiftcited by 7,005
  2. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166
  3. 2018How Does Batch Normalization Help Optimization?cited by 357
  4. 2018Model Evaluation, Model Selection, and Algorithm Selection in Machine Learningcited by 157
  5. 2019TouchVR: a Wearable Haptic Interface for VR Aimed at Delivering Multi-modal Stimuli at the User's Palmcited by 1

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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 1.

3 papers.