A Hermetic, Transparent Soft Growing Vine Robot System for Pipe Inspection
William E. Heap, Yimeng Qin, Kai Hammond, Anish Bayya, Haonon Kong, Allison M. Okamura
TL;DR
This work tackles in-pipe condition assessment for aging, non-branching pipes by introducing a hermetic, transparent soft growing vine robot that encloses all subsystems to enable internal visual sensing. A passively adapting enclosed tip mount keeps sensors at the moving tip while minimizing propulsion losses, and a canister-style base station simplifies deployment without active length control. The system is modeled and validated through lab tests and a real wastewater pipe deployment, demonstrating robust growth, sensing, and 3D pipe mapping capabilities with minimal external hardware. The approach reduces environmental interference, improves reliability in challenging pipe interiors, and provides a practical platform for future integration of advanced sensing and localization methods.
Abstract
Rehabilitation of aging pipes requires accurate condition assessment and mapping far into the pipe interiors. Soft growing vine robot systems are particularly promising for navigating confined, sinuous paths such as in pipes, but are currently limited by complex subsystems and a lack of validation in real-world industrial settings. In this paper, we introduce the concept and implementation of a hermetic and transparent vine robot system for visual condition assessment and mapping within non-branching pipes. This design encloses all mechanical and electrical components within the vine robot's soft, airtight, and transparent body, protecting them from environmental interference while enabling visual sensing. Because this approach requires an enclosed mechanism for transporting sensors, we developed, modeled, and tested a passively adapting enclosed tip mount. Finally, we validated the hermetic and transparent vine robot system concept through a real-world condition assessment and mapping task in a wastewater pipe. This work advances the use of soft-growing vine robots in pipe inspection by developing and demonstrating a robust, streamlined, field-validated system suitable for continued development and deployment.
