Self-growing robots are an emerging solution in soft robotics for navigating, exploring, and colonizing unstructured environments. However, their ability to grow and move in heterogeneous three-dimensional (3D) spaces, comparable with real-world conditions, is still developing. We present an autonomous growing robot that draws inspiration from the behavioral adaptive strategies of climbing plants to navigate unstructured environments. The robot mimics climbing plants’ apical shoot to sense and coordinate additive adaptive growth via an embedded additive manufacturing mechanism and a sensorized tip. Growth orientation, comparable with tropisms in real plants, is dictated by external stimuli, including gravity, light, and shade. These are incorporated within a vector field method to implement the preferred adaptive behavior for a given environment and task, such as growth toward light and/or against gravity. We demonstrate the robot’s ability to navigate through growth in relation to voids, potential supports, and thoroughfares in otherwise complex habitats. Adaptive twining around vertical supports can provide an escape from mechanical stress due to self-support, reduce energy expenditure for construction costs, and develop an anchorage point to support further growth and crossing gaps. The robot adapts its material printing parameters to develop a light body and fast growth to twine on supports or a tougher body to enable self-support and cross gaps. These features, typical of climbing plants, highlight a potential for adaptive robots and their on-demand manufacturing. They are especially promising for applications in exploring, monitoring, and interacting with unstructured environments or in the autonomous construction of complex infrastructures.

中文翻译：

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一种不断生长的软机器人，具有受攀爬植物启发的自适应行为，可在非结构化环境中导航

自我生长机器人是软机器人领域的一种新兴解决方案，用于导航、探索和殖民非结构化环境。然而，它们在与现实世界条件相当的异构三维 (3D) 空间中生长和移动的能力仍在发展中。我们提出了一种自主生长的机器人，它从攀爬植物的行为适应策略中汲取灵感，以适应非结构​​化环境。该机器人模仿攀缘植物的顶端芽，通过嵌入式增材制造机制和传感尖端来感知和协调增材适应性生长。与真实植物的向性相比，生长方向是由外部刺激决定的，包括重力、光线和阴影。这些被纳入矢量场方法中，以实现给定环境和任务的首选自适应行为，例如向光和/或逆重力生长。我们展示了机器人在复杂栖息地中通过与空隙、潜在支撑和通道相关的生长进行导航的能力。围绕垂直支撑的自适应缠绕可以逃避由于自支撑而产生的机械应力，减少建筑成本的能源消耗，并开发一个锚固点来支持进一步的生长和跨越间隙。该机器人调整其材料打印参数，以开发出轻质的身体并快速生长以缠绕在支撑物上或更坚固的身体上，以实现自我支撑和跨越间隙。这些攀爬植物的典型特征凸显了自适应机器人及其按需制造的潜力。它们特别适用于探索、监控和与非结构化环境交互或复杂基础设施的自主构建等应用。