Zero-Shot Transfer of Force Map Estimation Across GelSight Mini Sensors

2026-08-18

AI Summary

本文提出一种两阶段方法，通过域适应和U-Net网络解决不同GelSight Mini传感器间3D力图估计的标准化问题。

Abstract

Despite the rapid industrialization of the touch sensor manufacturing process, most of these sensors are still handmade in research laboratories. This complicates standardizing their performance, requiring the repetition of data collection and training models for each unit produced. To address this problem, this paper presents a method that can generalize the estimation of 3D force maps across different GelSight Mini sensor units, regardless of the sensor version. Specifically, the method consists of two stages: a domain adaptation stage, in which the input tactile image is reconstructed as a general tactile image using a UniT-based model; and a stage for estimating 3D force maps employing a U-Net network. Our proposal achieves promising results in both steps, such as an SSIM of 0.9338 +- 0.0358 in the image reconstruction phase and an MAE_F of 1.1294 +- 1.5934(N) in the force estimation phase.

Problem

• GelSight Mini
• sensor performance
• standardization
• data collection
• model training

Innovation

• Zero-Shot Transfer
• Force Map Estimation
• GelSight Mini Sensors
• Domain Adaptation
• U-Net Network