3 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…