Proactive Robotic Grasp Stability via Tactile Safety Margin Feedback

Robotic artificial intelligence requires an artificial tactile sensing system to enable delicate and adaptive task execution with robotic hands. Deformable electronic skin devices can function as a robotic skin, providing real‐time monitoring of grasping conditions during manipulation. However, grasp stability has traditionally been assessed only after slippage occurs, due to the lack of an effective feedback system. This work introduces the concept of tactile safety margin (TSM) for the first time, enabling proactive assessment of grasp stability while maintaining contact with target objects. This deterministic metric allows robots to adjust grip force or position to secure object manipulation before slippage occurs. Grasping instability is inferred from surface strain and temperature, both of which are concurrently detected by a deformable multimodal sensor array. The maximum static friction, derived from normal pressure, determines the range of mechanical instability the system can withstand. The integration of ionic multimodal sensor array and piezoresistive sensor array demonstrates independent responsivity to pressure, strain, and temperature within a simple and robust architecture. The effectiveness of TSM is validated through various robotic grasping scenarios, including dynamic thermal tests and pick‐and‐place tasks. This concept highlights a new role for deformable electronic skin in advancing robotic tactile sensing.