A Multi-Vine Soft Robot Enabling Accessible Working Channel and Steering

📅 2026-09-03
📈 Citations: 0
Influential: 0
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🤖 AI Summary
本文提出一种多藤状软体机器人架构,通过独立驱动实现尖端主动转向,并提供外部工作通道,以解决复杂环境下的导航和工具输送问题。
📝 Abstract
Soft eversion robots, also known as vine robots, have attracted growing interest for navigation and inspection tasks, including minimally invasive medical applications [1]. A vine robot consists of a thin, flexible, inextensible tube folded inward that everts and grows forward when pressurized. This tip-growth enables navigation with minimal friction, making vine robots well suited for complex environments such as the human colon [2]. While their inherent softness allows passive conforma- tion to curved pathways in confined spaces, navigation performance strongly depends on environmental inter- actions, including contact angle and the length of un- constrained deployed material [3], [4]. Sharp directional changes, such as those in the sigmoid colon, often limit passive growth and necessitate active steering. Existing solutions include distributed artificial muscles [5] or dedicated tip-based steering mechanisms [6]. In addition, many applications require payload delivery, such as sensors and tools [7], [8]. Within the ERC Synergy project EndoTheranostics, this motivates the development of vine robots capable of delivering micro- surgical tools during growth. Prior work has integrated working channels within the vine body [8], [9], but these approaches constrain tool size, introduce friction, and limit access to the environment to the robot tip. In this work, we propose a multi-vine architecture in which two vine robots are coupled to an externally integrated working channel via soft mounting tips [10]. Independent vine actuation enables active tip steering while advancing the working channel without embed- ding it within the vine bodies Figure 1. Experiments demonstrate sharp steering of nearly 90 degrees during growth, highlighting the potential of this architecture for versatile medical and non-medical applications.
Problem

Research questions and friction points this paper is trying to address.

soft eversion robots
steering
payload delivery
complex environments
active steering
Innovation

Methods, ideas, or system contributions that make the work stand out.

multi-vine architecture
active tip steering
external working channel
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Reza Kashef
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Mohammad Sheikh Sofla
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Kaspar Althoefer
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Professor of Robotics, Queen Mary University of London; Former Alan Turing Fellow; Director of ARQ
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