一种具有模块数自适应的模块化软机器人新型精确BiLSTM组态控制器。

Zixi Chen, Matteo Bernabei, Vanessa Mainardi, Xuyang Ren, Gastone Ciuti, Cesare Stefanini
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引用次数: 0

摘要

与单模组机器人相比,模块化软机器人(MSRs)在复杂任务中表现出更大的潜力。然而,模块化结构增加了精确控制的复杂性,需要针对模块化机器人制定专门的控制策略。在本文中,我们介绍了为MSR量身定制的数据收集策略和能够适应不同模块数量的双向长短期记忆(biLSTM)配置控制器。仿真缆索驱动机器人和真实的气动机器人已经在实验中验证了所提出的方法。实验结果表明,由于我们的数据收集方法,msr可以探索更大的空间,并且我们的控制器可以在模块数量增加或减少的情况下发挥作用。通过利用biLSTM,我们的目标是模拟msr的物理结构,允许控制器适应模块数量的变化。未来的工作可能包括一种规划方法,将任务、配置和驱动空间连接起来。我们也可以将在线组件集成到控制器中。
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A Novel and Accurate BiLSTM Configuration Controller for Modular Soft Robots with Module Number Adaptability.

Modular soft robots (MSRs) exhibit greater potential for sophisticated tasks compared with single-module robots. However, the modular structure incurs the complexity of accurate control and necessitates a control strategy specifically for modular robots. In this article, we introduce a data collection strategy tailored for MSR and a bidirectional long short-term memory (biLSTM) configuration controller capable of adapting to varying module numbers. Simulation cable-driven robots and real pneumatic robots have been included in experiments to validate the proposed approaches. Experimental results have demonstrated that MSRs can explore a larger space, thanks to our data collection method, and our controller can be leveraged despite an increase or decrease in module number. By leveraging the biLSTM, we aim to mimic the physical structure of MSRs, allowing the controller to adapt to module number change. Future work may include a planning method that bridges the task, configuration, and actuation spaces. We may also integrate online components into this controller.

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