Modular soft robots have shown higher potential in sophisticated tasks than single-module robots. However, the modular structure incurs the complexity of accurate control and necessitates a control strategy specifically for modular robots. In this paper, we introduce a data collection strategy and a novel and accurate bidirectional LSTM configuration controller for modular soft robots with module number adaptability. Such a controller can control module configurations in robots with different module numbers. Simulation cable-driven robots and real pneumatic robots have been included in experiments to validate the proposed approaches, and we have proven that our controller can be leveraged even with the increase or decrease of module number. This is the first paper that gets inspiration from the physical structure of modular robots and utilizes bidirectional LSTM for module number adaptability. Future work may include a planning method that bridges the task and configuration spaces and the integration of an online controller.

翻译：模块化软体机器人在复杂任务中展现出比单模块机器人更高的潜力。然而，模块化结构带来了精确控制的复杂性，亟需专门针对模块化机器人的控制策略。本文提出了一种数据收集策略，以及一种新颖且精确的、具有模块数量适应性的双向LSTM配置控制器，用于模块化软体机器人。该控制器能够控制具有不同模块数量的机器人中的模块配置。实验通过仿真缆驱动机器人和真实气动机器人验证了所提方法，并证明即使模块数量增加或减少，该控制器仍然有效。本文是首篇受模块化机器人物理结构启发、利用双向LSTM实现模块数量适应性的研究。未来工作可能包括连接任务空间与配置空间的规划方法，以及在线控制器的集成。