Many lower-limb exoskeletons have been developed to assist gait, exhibiting a large range of control methods. The goal of this paper is to review and classify these control strategies, that determine how these devices interact with the user. In addition to covering the recent publications on the control of lower-limb exoskeletons for gait assistance, an effort has been made to review the controllers independently of the hardware and implementation aspects. The common 3-level structure (high, middle, and low levels) is first used to separate the continuous behavior (mid-level) from the implementation of position/torque control (low-level) and the detection of the terrain or user’s intention (high-level). Within these levels, different approaches (functional units) have been identified and combined to describe each considered controller. 291 references have been considered and sorted by the proposed classification. The methods identified in the high-level are manual user input, brain interfaces, or automatic mode detection based on the terrain or user’s movements. In the mid-level, the synchronization is most often based on manual triggers by the user, discrete events (followed by state machines or time-based progression), or continuous estimations using state variables. The desired action is determined based on position/torque profiles, model-based calculations, or other custom functions of the sensory signals. In the low-level, position or torque controllers are used to carry out the desired actions. In addition to a more detailed description of these methods, the variants of implementation within each one are also compared and discussed in the paper. By listing and comparing the features of the reviewed controllers, this work can help in understanding the numerous techniques found in the literature. The main identified trends are the use of pre-defined trajectories for full-mobilization and event-triggered (or adaptive-frequency-oscillator-synchronized) torque profiles for partial assistance. More recently, advanced methods to adapt the position/torque profiles online and automatically detect terrains or locomotion modes have become more common, but these are largely still limited to laboratory settings. An analysis of the possible underlying reasons of the identified trends is also carried out and opportunities for further studies are discussed.

中文翻译：

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下肢外骨骼辅助步态控制策略综述

已经开发了许多下肢外骨骼来辅助步态，展示了多种控制方法。本文的目的是审查和分类这些控制策略，以确定这些设备如何与用户交互。除了涵盖最近关于控制下肢外骨骼以进行步态辅助的出版物外，还努力独立于硬件和实施方面来审查控制器。常用的 3 级结构（高、中、低级）首先用于将连续行为（中级）与位置/扭矩控制（低级）的实现以及对地形或用户意图的检测分开（高水平）。在这些级别中，已经确定并组合了不同的方法（功能单元）来描述每个考虑的控制器。291 篇参考文献已按照建议的分类进行了考虑和排序。高级中确定的方法是手动用户输入、大脑接口或基于地形或用户运动的自动模式检测。在中层，同步通常基于用户手动触发、离散事件（随后是状态机或基于时间的进程）或使用状态变量的连续估计。期望的动作是基于位置/扭矩曲线、基于模型的计算或其他感官信号的自定义函数来确定的。在低级，位置或扭矩控制器用于执行所需的动作。除了对这些方法进行更详细的描述外，本文还比较和讨论了每种方法中的实现变体。通过列出和比较所审查控制器的特性，这项工作可以帮助理解文献中发现的众多技术。主要确定的趋势是使用预定义的轨迹进行全面动员和事件触发（或自适应频率振荡器同步）扭矩曲线用于部分辅助。最近，在线调整位置/扭矩曲线和自动检测地形或运动模式的先进方法变得更加普遍，但这些方法在很大程度上仍仅限于实验室设置。还对已确定趋势的可能根本原因进行了分析，并讨论了进一步研究的机会。主要确定的趋势是使用预定义的轨迹进行全面动员和事件触发（或自适应频率振荡器同步）扭矩曲线用于部分辅助。最近，在线调整位置/扭矩曲线和自动检测地形或运动模式的先进方法变得更加普遍，但这些方法在很大程度上仍仅限于实验室设置。还对已确定趋势的可能根本原因进行了分析，并讨论了进一步研究的机会。主要确定的趋势是使用预定义的轨迹进行全面动员和事件触发（或自适应频率振荡器同步）扭矩曲线用于部分辅助。最近，在线调整位置/扭矩曲线和自动检测地形或运动模式的先进方法变得更加普遍，但这些方法在很大程度上仍仅限于实验室设置。还对已确定趋势的可能根本原因进行了分析，并讨论了进一步研究的机会。在线调整位置/扭矩曲线和自动检测地形或运动模式的先进方法已经变得更加普遍，但这些在很大程度上仍仅限于实验室设置。还对已确定趋势的可能根本原因进行了分析，并讨论了进一步研究的机会。在线调整位置/扭矩曲线和自动检测地形或运动模式的先进方法已经变得更加普遍，但这些在很大程度上仍仅限于实验室设置。还对已确定趋势的可能根本原因进行了分析，并讨论了进一步研究的机会。