5 papers
Learning the sense of touch in simulation: a sim-to-real strategy for vision-based tactile sensing
Carmelo Sferrazza, Thomas Bi, Raffaello D'Andrea
Data-driven approaches to tactile sensing aim to overcome the complexity of accurately modeling contact with soft materials. However, their widespread adoption is impaired by conce…
Towards vision-based robotic skins: a data-driven, multi-camera tactile sensor
Camill Trueeb, Carmelo Sferrazza, Raffaello D'Andrea
This paper describes the design of a multi-camera optical tactile sensor that provides information about the contact force distribution applied to its soft surface. This informatio…
Vision-Based Proprioceptive Sensing for Soft Inflatable Actuators
Peter Werner, Matthias Hofer, Carmelo Sferrazza +1
This paper presents a vision-based sensing approach for a soft linear actuator, which is equipped with an integrated camera. The proposed vision-based sensing pipeline predicts the…
Ground truth force distribution for learning-based tactile sensing: a finite element approach
Carmelo Sferrazza, Adam Wahlsten, Camill Trueeb +1
Skin-like tactile sensors provide robots with rich feedback related to the force distribution applied to their soft surface. The complexity of interpreting raw tactile information…
Transfer learning for vision-based tactile sensing
Carmelo Sferrazza, Raffaello D'Andrea
Due to the complexity of modeling the elastic properties of materials, the use of machine learning algorithms is continuously increasing for tactile sensing applications. Recent ad…