CommentsPaper accepted at IEEE/ACM ESWEEK (CODES) 2026. Authors' version posted for personal use and not for redistribution. The definitive version of the paper will appear in IEEE Embedded Systems Letters
机构
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Control/Robotics Research Laboratory (CRRL), Department of Electrical and Computer Engineering, NYU Tandon School of Engineering(纽约大学坦登工程学院电气与计算机工程系控制/机器人研究实验室(CRRL))
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New York University Abu Dhabi (NYUAD) Center for Artificial Intelligence and Robotics (CAIR)(纽约大学阿布扎比分校人工智能与机器人中心(CAIR))
机构
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State Key Laboratory of Fluid Power and Mechatronic Systems, Zhejiang University(浙江大学流体动力与机电系统国家重点实验室)
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Zhejiang Key Laboratory of Industrial Big Data and Robot Intelligent Systems(浙江省工业大数据与机器人智能系统重点实验室)
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School of Mechanical Engineering, Zhejiang University(浙江大学机械工程学院)
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Robotics Institute, Zhejiang University(浙江大学机器人研究院)
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School of Artificial Intelligence and Robotics, Hunan University(湖南大学人工智能与机器人学院)
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Rural Health Research Institute, Charles Sturt University(查尔斯特大学农村健康研究所)
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University College London(伦敦大学学院)
Learning Control as Enabling Layer for Embodied Intelligence Research explored with Soft Robotic Swimming in diverse Flow Speeds
学习控制作为具身智能研究的使能层:以软体机器人在不同流速下游泳为例
Fabian Schwab, Federico Allione, Bingcheng Wang, Mohamed El Arayshi, Claudio Mucignat, Ivan Lunati, Cristiano Verrelli, Ardian Jusufi
机构
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Engineering Sciences Department, Swiss Federal Laboratories for Materials Science and Technology(瑞士联邦材料科学与技术实验室工程科学系)
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Institute for NeuroInformatics, University of Zurich(苏黎世大学神经信息研究所)
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Department of Electronic Engineering, University of Rome Tor Vergata(罗马大学Tor Vergata电子工程系)