The ability to associate touch with other modalities has huge implications for humans and
computational systems. However multimodal learning with touch remains challenging due to …

Executing contact-rich manipulation tasks necessitates the fusion of tactile and visual
feedback. However, the distinct nature of these modalities poses significant challenges. In …

We introduce a novel approach that combines tactile estimation and control for in-hand
object manipulation. By integrating measurements from robot kinematics and an image …

We introduce a novel approach that combines tactile estimation and control for in-hand
object manipulation. By integrating measurements from robot kinematics and an image …

Predicting the consequences of the agent's actions on its environment is a pivotal challenge
in robotic learning, which plays a key role in developing higher cognitive skills for intelligent …

Dexterous manipulation of unknown objects performed by robots equipped with mechanical
hands represents a critical challenge. The difficulties arise from the absence of a precise …

We introduce a novel approach that combines tactile estimation and control for in-hand
object manipulation. By integrating measurements from robot kinematics and an image …

The development of vision-based tactile sensors has significantly enhanced robots'
perception and manipulation capabilities, especially for tasks requiring contact-rich …

This thesis introduces the concept of TEXterity (Tactile Extrinsic deXterity) to address
challenges in robotic manipulation. Focusing on tactile sensing, TEXterity aims to enhance …