Gotta Grow Fast: Design and Benchmarking of a Tip Mount for High-Speed Vine Robots

2026-06-04

AI Summary

This study addresses the challenge of stably mounting sensors such as cameras on soft vine robots during high-speed growth, which is hindered by continuous tip material deposition, interlayer friction, added payloads, and fabric constraints. To overcome this, the authors propose a triangular roller-based tip-mounting mechanism that replaces sliding with rolling contact, significantly reducing internal resistance and trailing tension. Built upon a TPU-coated, tear-resistant nylon platform, this design enables, for the first time, stable inverted growth and establishes a reproducible benchmarking framework for evaluating tip-mounted payload performance. Experimental results demonstrate substantially improved growth repeatability, providing a robust hardware foundation for integrating sensors and tools onto soft growing robots. The associated CAD designs have been made openly available.

Abstract

Soft, growing vine robots extend through tip eversion, a mechanism that enables navigation through cluttered environments. However, integrating cameras and other sensors at the tip is uniquely challenging because the material forming the tip is constantly renewed as the robot grows. This continual material turnover, combined with friction between internal layers, added tip weight, and fabric constriction, complicates sensor and tool mounting. These limitations hinder the deployment of vine robots for inspection and search tasks, where rapid growth while carrying tip-mounted sensors is essential. In this work, we present a triangular roller tip mount that reduces internal resistance during growth by rolling rather than sliding against the robot body. The design was refined through iterative failure analysis, enabling, for the first time, consistent eversion on a TPU-coated ripstop nylon vine robot. To quantitatively evaluate mount performance, we introduce a custom testbed that isolates tip mounting effects by measuring tail tension during eversion. Comparative experiments across multiple mount variants, including prior designs, show that our triangular roller mount achieves the lowest tail tension and most repeatable growth performance. These results establish both a validated tip mount design and a repeatable benchmarking framework for advancing sensor and tool integration in soft growing robots. CAD for the mount and testbed is available at: https://sprout-mitll.github.io/tip_mounts/.

Problem

• soft growing robots
• tip mounting
• sensor integration
• tip eversion
• vine robots

Innovation

• soft growing robots
• tip mount
• eversion
• friction reduction
• benchmarking framework