{"title":"Environmental Adaptation Enabled by an Amplitude-Tunable Traveling Wave Robot With a Soft Corkscrew (ATWBot)","authors":"Qinjie Ji;Aiguo Song;Sareum Kim;Josie Hughes","doi":"10.1109/TRO.2026.3697245","DOIUrl":null,"url":null,"abstract":"Amplitude tuning is an important strategy in animals employing traveling wave patterns, enhancing their adaptability to unstructured environments. This article proposes, for the first time, an amplitude tuning method that leverages the compliance of a soft corkscrew by twisting its ends. An amplitude tunable traveling wave robot (ATWBot) is developed, consisting of a soft corkscrew housed in a high-degree-of-freedom cage and driven by only two servos. The soft corkscrew and cage are monolithically 3D-printed. The ATWBot achieves a wide range of active amplitude tuning with passive compliance adaptation and can extend its morphology to a coiled configuration, enabling clamping and rolling. A comprehensive model is built for the twisted soft corkscrew geometry, proving that the robot’s speed is decoupled from amplitude variations during twisting. A genetic algorithm is used to optimize the soft corkscrew for achieving the fastest speed while matching the cage geometry. Experiments demonstrate that the combination of active amplitude tuning and passive body compliance enables the robot to adapt to unstructured terrains including slits, steps, gaps, converging tunnels, slopes, and swimming.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"2231-2248"},"PeriodicalIF":11.1000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11536812","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Robotics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11536812/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/3/27 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Amplitude tuning is an important strategy in animals employing traveling wave patterns, enhancing their adaptability to unstructured environments. This article proposes, for the first time, an amplitude tuning method that leverages the compliance of a soft corkscrew by twisting its ends. An amplitude tunable traveling wave robot (ATWBot) is developed, consisting of a soft corkscrew housed in a high-degree-of-freedom cage and driven by only two servos. The soft corkscrew and cage are monolithically 3D-printed. The ATWBot achieves a wide range of active amplitude tuning with passive compliance adaptation and can extend its morphology to a coiled configuration, enabling clamping and rolling. A comprehensive model is built for the twisted soft corkscrew geometry, proving that the robot’s speed is decoupled from amplitude variations during twisting. A genetic algorithm is used to optimize the soft corkscrew for achieving the fastest speed while matching the cage geometry. Experiments demonstrate that the combination of active amplitude tuning and passive body compliance enables the robot to adapt to unstructured terrains including slits, steps, gaps, converging tunnels, slopes, and swimming.
期刊介绍:
The IEEE Transactions on Robotics (T-RO) is dedicated to publishing fundamental papers covering all facets of robotics, drawing on interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, and beyond. From industrial applications to service and personal assistants, surgical operations to space, underwater, and remote exploration, robots and intelligent machines play pivotal roles across various domains, including entertainment, safety, search and rescue, military applications, agriculture, and intelligent vehicles.
Special emphasis is placed on intelligent machines and systems designed for unstructured environments, where a significant portion of the environment remains unknown and beyond direct sensing or control.