Soft, vine-inspired growing robots that move by eversion are highly mobile in confined environments, but, when faced with gaps in the environment, they may collapse under their own weight while navigating a desired path. In this work, we present a comprehensive collapse model that can predict the collapse length of steered robots in any shape using true shape information and tail tension. We validate this model by collapsing several unsteered robots without true shape information. The model accurately predicts the trends of those experiments. We then attempt to collapse a robot steered with a single actuator at different orientations. Our models accurately predict collapse when it occurs. Finally, we demonstrate how this could be used in the field by having a robot attempt a gap-crossing task with and without inflating its actuators. The robot needs its actuators inflated to cross the gap without collapsing, which our model supports. Our model has been specifically tested on straight and series pouch motor-actuated robots made of non-stretchable material, but it could be applied to other robot variations. This work enables us to model the robot's collapse behavior in any open environment and understand the parameters it needs to succeed in 3D navigation tasks.

翻译：基于藤蔓仿生原理、通过外翻运动实现位移的软体生长机器人，在受限环境中展现出高度机动性。然而，当面临环境中的间隙时，机器人在沿预定路径行进过程中可能因自重发生坍塌。本研究提出了一种综合坍塌模型，该模型可利用真实形态信息与尾部张力，预测任意形态转向机器人的坍塌长度。我们通过使多个未转向且缺乏真实形态信息的机器人发生坍塌，验证了该模型的可靠性。模型准确预测了这些实验的趋势变化。随后，我们尝试使配备单执行器的转向机器人在不同取向下发生坍塌，模型在坍塌发生时均能作出精确预测。最后，我们通过让机器人在充气与未充气状态下执行越障任务，演示了该模型的实际应用价值：机器人需充气执行器方能跨越间隙而不坍塌，这与模型预测结果一致。本模型已在由非拉伸材料制成的直筒型及串联囊式电机驱动机器人上完成专项测试，但其同样适用于其他机器人变体。此项研究使我们能够模拟机器人在任意开放环境中的坍塌行为，并理解其在三维导航任务中取得成功所需的关键参数。