6 accepted papers
While tactile sensing is widely accepted as an important and useful sensing modality, its use pales in comparison to other sensory modalities like vision and proprioception. AnySkin addresses the critical challenges that impede the use of tactile sensing - versatility, replaceability, and data reusa
Recent progress in reinforcement learning (RL) and tactile sensing has significantly advanced dexterous manipulation. However, these methods often utilize simplified tactile signals due to the gap between tactile simulation and the real world. We introduce a sensor model for tactile skin that enable
High cost and lack of reliability have precluded the widespread adoption of dexterous hands in robotics. Furthermore, the lack of a viable tactile sensor capable of sensing over the entire area of the hand impedes the rich, low-level feedback that would improve the learning of dexterous manipulation
Soft tactile skins can provide an in-depth understanding of contact location and force through a soft and deformable interface. However, widespread implementation of soft robotic sensing skins remains limited due to non-scalable fabrication techniques, lack of customization, and complex integration
As the use of soft robotics and soft actuators becomes more popular, there is also an increased need for soft sensors that can perform robustly under various extreme conditions. While some applications find ultrathin flexible sensors sufficient, like electronic skin and wearable devices, there is st
Recent advances in soft sensors using microfluidic liquid conductors enabled sensing of large deformation of soft structures. However, the use of liquids as conductive media carries a risk of leakage in many cases. Furthermore, it could be harmful when exposed to the human body in certain applicatio…