activity
20202023
collaborators

5 papers

cs.RO2023

TIAGo RL: Simulated Reinforcement Learning Environments with Tactile Data for Mobile Robots

Luca Lach, Francesco Ferro, Robert Haschke

Tactile information is important for robust performance in robotic tasks that involve physical interaction, such as object manipulation. However, with more data included in the rea…

cs.RO2023

Bio-Inspired Grasping Controller for Sensorized 2-DoF Grippers

Luca Lach, Séverin Lemaignan, Francesco Ferro +2

We present a holistic grasping controller, combining free-space position control and in-contact force-control for reliable grasping given uncertain object pose estimates. Employing…

cs.RO2023

Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot

Luca Lach, Robert Haschke, Davide Tateo +4

The advent of tactile sensors in robotics has sparked many ideas on how robots can leverage direct contact measurements of their environment interactions to improve manipulation ta…

cs.RO2022

Placing by Touching: An empirical study on the importance of tactile sensing for precise object placing

Luca Lach, Niklas Funk, Robert Haschke +4

This work deals with a practical everyday problem: stable object placement on flat surfaces starting from unknown initial poses. Common object-placing approaches require either com…

cs.RO2020

Leveraging Touch Sensors to Improve Mobile Manipulation

Luca Lach, Robert Haschke, Francesco Ferro +1

Despite many advances in service robotics, successful and secure object manipulation on mobile platforms is still a challenge. In order to come closer to human grasping performance…