8 papers
Apple: Toward General Active Perception via Reinforcement Learning
Tim Schneider, Cristiana de Farias, Roberto Calandra +2
Active perception is a fundamental skill that enables us humans to deal with uncertainty in our inherently partially observable environment. For senses such as touch, where the inf…
On the Importance of Tactile Sensing for Imitation Learning: A Case Study on Robotic Match Lighting
Niklas Funk, Changqi Chen, Tim Schneider +3
The field of robotic manipulation has advanced significantly in recent years. At the sensing level, several novel tactile sensors have been developed, capable of providing accurate…
Tactile-Conditioned Diffusion Policy for Force-Aware Robotic Manipulation
Erik Helmut, Niklas Funk, Tim Schneider +2
Contact-rich manipulation depends on applying the correct grasp forces throughout the manipulation task, especially when handling fragile or deformable objects. Most existing imita…
Tactile MNIST: Benchmarking Active Tactile Perception
Tim Schneider, Guillaume Duret, Cristiana de Farias +3
Tactile perception has the potential to significantly enhance dexterous robotic manipulation by providing rich local information that can complement or substitute for other sensory…
Investigating Active Sampling for Hardness Classification with Vision-Based Tactile Sensors
Junyi Chen, Alap Kshirsagar, Frederik Heller +7
One of the most important object properties that humans and robots perceive through touch is hardness. This paper investigates information-theoretic active sampling strategies for…
Towards Safe Robot Foundation Models Using Inductive Biases
Maximilian Tölle, Theo Gruner, Daniel Palenicek +6
Safety is a critical requirement for the real-world deployment of robotic systems. Unfortunately, while current robot foundation models show promising generalization capabilities a…