Spiders use adhesive, stretchable, and translucent webs to capture their prey. However, sustaining the capturing capability of these webs can be challenging because the webs inevitably invite contamination, thus reducing its adhesion force. To overcome these challenges, spiders have developed strategies of using webs to sense prey and clean contaminants. Here, we emulate the capturing strategies of a spider with a single pair of ionic threads based on electrostatics. Our ionic spiderwebs completed consecutive missions of cleaning contamination on itself, sensing approaching targets, capturing those targets, and releasing them. The ionic spiderwebs demonstrate the importance of learning from nature and push the boundaries of soft robotics in an attempt to combine mutually complementary functions into a single unit with a simple structure.

蜘蛛使用粘性，可拉伸和半透明的网捕获猎物。然而，维持这些纤维网的捕获能力可能是具有挑战性的，因为纤维网不可避免地会引起污染，从而降低其粘附力。为了克服这些挑战，蜘蛛公司已经开发出了使用网来感知猎物​​和清除污染物的策略。在这里，我们模拟了具有一对基于静电的离子线的蜘蛛的捕获策略。我们的离子蜘蛛网完成了连续的任务，即清除自身的污染物，感应接近的目标，捕获这些目标并释放它们。离子蜘蛛网展示了从自然界学习的重要性，并突破了软机器人的界限，试图将相互补充的功能组合成具有简单结构的单个单元。