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Xuanxuan Yang

4 accepted papers

2025

Enhancing Tactile Sensing in Robotics Using Null-Space Diffusion Model with EIT-based Sensors

IROS 2025

Robotic tactile sensors based on Electrical Impedance Tomography (EIT) have gained great attention in robotic sensing applications due to their features such as no internal wiring, "all-in-one" structure, and continuous sensing capabilities. However, the effectiveness of EIT-based tactile sensors is

Cited by 0SourceScholar
2024

Correcting Non-Uniform Sensitivity in EIT Tactile Sensing via Jacobian Vector Approximation

RA-L 2024

Electrical impedance tomography (EIT)-based tactile sensors enable promising capabilities for safe human-robot interaction through large-area distributed force sensing. However, their practical realization is hampered by non-uniform sensitivity distribution which varies at different locations. This

Cited by 9SourceScholar
2024

Enhancing Tactile Sensing in Robotics: Dual-Modal Force and Shape Perception with EIT-based Sensors and MM-CNN

ICRA 2024poster

Electrical Impedance Tomography (EIT)-based tactile sensors offer durability, scalability, and cost-effective manufacturing. However, simultaneously reconstructing force and shape from boundary measurements remains challenging due to EIT’s inherent location dependencies and image artifacts. This stu…

Cited by 2SourceScholar
2024

Pseudo-Domain Adversarial Networks with Electrical Impedance Tomography for Electrode Offset Error

IROS 2024poster

This paper propose a novel transfer learning approach, Pseudo-Domain Adversarial Network (PDAN), to tackle the issue of electrode displacement in Electrical Impedance Tomography (EIT). Electrode displacement, caused by human movement or improper operation, significantly affects the accuracy of EIT b…

Cited by 0SourceScholar