Tactile Sensor

Tactile sensors aim to replicate the human sense of touch in robotic systems, enabling robots to perceive contact forces, shapes, textures, and temperatures. Current research emphasizes developing more versatile, affordable, and easily integrable sensors, often employing vision-based systems, soft materials, and magnetic or capacitive sensing principles. Machine learning, particularly neural networks (including transformers and recurrent graph neural networks), and physics-based modeling (like finite element methods) are crucial for processing sensor data and reconstructing complex tactile information. These advancements are significantly impacting robotics, enabling more dexterous manipulation, improved object recognition, and safer human-robot interaction in diverse applications.