Leveraging Touch Sensors to Improve Mobile Manipulation. - Luca Lach; Robert Haschke; Francesco Ferro; Jordi Pagès (CoRR, 2020)

Guiding Representation Learning in Deep Generative Models with Policy Gradients. - Luca Lach; Timo Korthals; Francesco Ferro; Helge J. Ritter; Malte Schilling (OLA, 2021)

Using Tactile Sensing to Improve the Sample Efficiency and Performance of Deep Deterministic Policy Gradients for Simulated In-Hand Manipulation Tasks. - Andrew Melnik; Luca Lach; Matthias Plappert; Timo Korthals; Robert Haschke; Helge J. Ritter (Frontiers Robotics AI, 2021)

Bio-Inspired Grasping Controller for Sensorized 2-DoF Grippers. - Luca Lach; Séverin Lemaignan; Francesco Ferro; Helge J. Ritter; Robert Haschke (IROS, 2022)

Placing by Touching: An Empirical Study on the Importance of Tactile Sensing for Precise Object Placing. - Luca Lach; Niklas Funk; Robert Haschke; Séverin Lemaignan; Helge Joachim Ritter; Jan Peters 001; Georgia Chalvatzaki (IROS, 2023)

Towards Transferring Tactile-based Continuous Force Control Policies from Simulation to Robot. - Luca Lach; Robert Haschke; Davide Tateo; Jan Peters 001; Helge J. Ritter; Júlia Borràs Sol; Carme Torras (CoRR, 2023)

TIAGo RL: Simulated Reinforcement Learning Environments with Tactile Data for Mobile Robots. - Luca Lach; Francesco Ferro; Robert Haschke (CoRR, 2023)

Zero-Shot Transfer of a Tactile-based Continuous Force Control Policy from Simulation to Robot. - Luca Lach; Robert Haschke; Davide Tateo; Jan Peters 001; Helge J. Ritter; Júlia Borràs Sol; Carme Torras (IROS, 2024)

Learning When to Stop: Efficient Active Tactile Perception with Deep Reinforcement Learning. - Christopher Niemann; David P. Leins; Luca Lach; Robert Haschke (IROS, 2024)