# Pose-Based Tactile Servoing: Controlled Soft Touch using Deep Learning

arXiv: https://arxiv.org/abs/2012.02504 · HTML: https://mlsanity.com/paper/2012.02504/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2020.

## Built on by (most cited first, 6 of 6)

- [Tactile Sim-to-Real Policy Transfer via Real-to-Sim Image Translation](https://mlsanity.com/paper/2106.08796/) (2021)
- [Attention for Robot Touch: Tactile Saliency Prediction for Robust Sim-to-Real Tactile Control](https://mlsanity.com/paper/2307.14510/) (2023)
- [TacPAC: Tactile Prediction and Real-Time Action Correction in World-Action Models for Contact-Rich Manipulation](https://mlsanity.com/paper/2609.05266/) (2026)
- [Semi-Supervised Disentanglement of Tactile Contact~Geometry from Sliding-Induced Shear](https://mlsanity.com/paper/2208.12500/) (2022)
- [Monocular Reconstruction of Neural Tactile Fields](https://mlsanity.com/paper/2602.12508/) (2026)
- [MultiDiffSense: Diffusion-Based Multi-Modal Visuo-Tactile Image Generation Conditioned on Object Shape and Contact Pose](https://mlsanity.com/paper/2602.19348/) (2026)

## Abstract (arXiv)

This article describes a new way of controlling robots using soft tactile sensors: pose-based tactile servo (PBTS) control. The basic idea is to embed a tactile perception model for estimating the sensor pose within a servo control loop that is applied to local object features such as edges and surfaces. PBTS control is implemented with a soft curved optical tactile sensor (the BRL TacTip) using a convolutional neural network trained to be insensitive to shear. In consequence, robust and accurate controlled motion over various complex 3D objects is attained. First, we review tactile servoing and its relation to visual servoing, before formalising PBTS control. Then, we assess tactile servoing over a range of regular and irregular objects. Finally, we reflect on the relation to visual servo control and discuss how controlled soft touch gives a route towards human-like dexterity in robots.