A design and prototyping method for pre-shaped soft growing robots based on material patching
Year: 2026
Type: article
Abstract: In this paper, we propose a novel, simple and effective design and prototyping method to realize pre-shaped soft growing robots (SGRs) enabled by material patching. By attaching two elastic and differently pre-tensioned fabric sheets, a tubular robot body segment is prototyped to realize a pre-determined constant-curvature shape. Multiple segments are then assembled sequentially to create SGRs that can grow along complex continuous shapes. We present the working principle, the equivalent kinematic model, a task-specific design tool for patched SGRs, and the prototyping method. Then, we evaluate the patched SGR capabilities, and compare them with respect to the most widespread pre-steered SGRs’ fabrication method, known as pinching. The evaluation is performed in terms of amount of utilized body material (15.3% reduction), mechanical properties (up to 7.3 times stiffer) and capability to carry tip-mounted payloads. Finally, we deployed a single-segment pre-shaped prototype in two different case studies, showing the capability of a single-patched SGR to handle remote visual inspection and cable-delivery in known constrained environments, achieving 81.7% and 68.3% faster completion times than manual procedures. • We propose a novel design and prototyping method for pre-shaped soft growing robots. • We introduce a 2D kinematic model and design tool for collision-free patched SGRs. • We demonstrate that our method reduces body material up to 15.3% for a fixed target. • We demonstrate that patched SGR exhibits up to 7.3 times higher stiffness than SoA. • We validate for two different tasks with up to 81.7% faster completion.
Institution: University of Naples Federico II
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,950
Funder: European Commission
Awards: G1585674959, G482427013
OpenAlex ID: W7138853249
