Everting, soft growing vine robots benefit from reduced friction with their environment, which allows them to navigate challenging terrain. Vine robots can use air pouches attached to their sides for lateral steering. However, when all pouches are serially connected, the whole robot can only perform one constant curvature in free space. It must contact the environment to navigate through obstacles along paths with multiple turns. This work presents a multi-segment vine robot that can navigate complex paths without interacting with its environment. This is achieved by a new steering method that selectively actuates each single pouch at the tip, providing high degrees of freedom with few control inputs. A small magnetic valve connects each pouch to a pressure supply line. A motorized tip mount uses an interlocking mechanism and motorized rollers on the outer material of the vine robot. As each valve passes through the tip mount, a permanent magnet inside the tip mount opens the valve so the corresponding pouch is connected to the pressure supply line at the same moment. Novel cylindrical pneumatic artificial muscles (cPAMs) are integrated into the vine robot and inflate to a cylindrical shape for improved bending characteristics compared to other state-of-the-art vine robots. The motorized tip mount controls a continuous eversion speed and enables controlled retraction. A final prototype was able to repeatably grow into different shapes and hold these shapes. We predict the path using a model that assumes a piecewise constant curvature along the outside of the multi-segment vine robot. The proposed multi-segment steering method can be extended to other soft continuum robot designs.

翻译：外翻式的软体生长藤蔓机器人因其与环境的摩擦较小，从而能够穿越复杂地形。此类机器人可利用侧面附着的空气囊袋实现横向转向。然而，当所有气囊串联连接时，整个机器人仅在自由空间中具有单一恒定曲率，必须接触环境才能沿多转弯路径绕过障碍物。本研究提出一种无需与环境交互即可穿越复杂路径的多段式藤蔓机器人。该目标通过一种新型转向方法实现：该方法选择性地驱动顶端每个独立气囊，以少量控制输入获得高自由度。每个气囊通过小型电磁阀连接至压力供应管路。电机驱动的顶端支架采用互锁机构及作用在藤蔓机器人外层材料上的电动滚轮。当每个阀门通过顶端支架时，支架内的永磁体会开启阀门，使对应气囊在同一时刻接入压力供应管路。新型圆柱形气动人工肌肉（cPAMs）被集成至藤蔓机器人中，充气后呈圆柱形，相比其他先进藤蔓机器人表现出更优的弯曲特性。电机驱动的顶端支架可控制连续外翻速度并实现受控回缩。最终原型能够重复生长为不同形状并保持该形状。我们采用基于多段式藤蔓机器人外部分段恒定曲率假设的模型预测其路径。所提出的多段式转向方法可扩展至其他软体连续体机器人设计。