Smart adhesion actuators have played an increasingly important role in industrial manufacturing, medical equipment, and other applications of daily life. Inspired by the octopus sucker, a smart bionic adhesion actuator is designed that uses hydrogel-based materials with a photothermal effect to simulate the contraction and relaxation of octopus sucker muscles, enabling it to rapidly grasp and release objects weighing more than 24 times its own weight, while having good cyclic stability. The magnitude of the grasping force can be monitored in real time through an additional sensing structure, which is similar to the nerves of octopus sucker. By sensing and adjusting the state of adsorption, controllable adsorption can be achieved using this self-sensing function, thereby greatly improving energy efficiency. It provides a new direction for the design of smart bionic adhesion actuators with hydrogels.
Replicating human somatosensory networks in robots is crucial for dexterous manipulation, ensuring the appropriate grasping force for objects of varying softness and textures. Despite advances in artificial haptic sensing for object recognition, accurately quantifying haptic perceptions to discern softness and texture remains challenging. Here, we report a methodology that uses a bimodal haptic sensor to capture multidimensional static and dynamic stimuli, allowing for the simultaneous quantification of softness and texture features. This method demonstrates synergistic measurements of elastic and frictional coefficients, thereby providing a universal strategy for acquiring the adaptive gripping force necessary for scarless, antislippage interaction with delicate objects. Equipped with this sensor, a robotic manipulator identifies porcine mucosal features with 98.44% accuracy and stably grasps visually indistinguishable mature white strawberries, enabling reliable tissue palpation and intelligent picking. The design concept and comprehensive guidelines presented would provide insights into haptic sensor development, promising benefits for robotics.