4 papers
Embodiment-Agnostic Navigation Policy Trained with Visual Demonstrations
Nimrod Curtis, Osher Azulay, Avishai Sintov
Learning to navigate in unstructured environments is a challenging task for robots. While reinforcement learning can be effective, it often requires extensive data collection and c…
Visuotactile-Based Learning for Insertion with Compliant Hands
Osher Azulay, Dhruv Metha Ramesh, Nimrod Curtis +1
Compared to rigid hands, underactuated compliant hands offer greater adaptability to object shapes, provide stable grasps, and are often more cost-effective. However, they introduc…
Augmenting Tactile Simulators with Real-like and Zero-Shot Capabilities
Osher Azulay, Alon Mizrahi, Nimrod Curtis +1
Simulating tactile perception could potentially leverage the learning capabilities of robotic systems in manipulation tasks. However, the reality gap of simulators for high-resolut…
AllSight: A Low-Cost and High-Resolution Round Tactile Sensor with Zero-Shot Learning Capability
Osher Azulay, Nimrod Curtis, Rotem Sokolovsky +4
Tactile sensing is a necessary capability for a robotic hand to perform fine manipulations and interact with the environment. Optical sensors are a promising solution for high-reso…