Underwater Soft Robot Modeling and Control With Differentiable Simulation
Underwater Soft Robot Modeling and Control With Differentiable Simulation
复制标题
DOI：
10.1109/lra.2021.3070305
复制
发表时间：
2021-07-01
影响因子：
5.2
通讯作者：
Rus, Daniela
中科院分区：
文献类型：
--
作者：
Du, Tao;Hughes, Josie;Rus, Daniela
水下软机器人由于其高度的自由度和与水的复杂耦合，在建模和控制方面具有挑战性。在这封信中，我们提出了一种方法，该方法利用可微模拟的最新发展与可微的、解析的水动力学模型相结合来辅助水下软机器人的建模和控制。我们将这种方法应用于海星，这是一种定制的软机器人设计，易于制造，操作起来也很直观。我们的方法从从真实机器人获得的数据开始，在模拟和实验之间交替进行。具体来说，仿真步骤使用可微仿真器的梯度进行系统辨识和轨迹优化，实验步骤对机器人执行优化后的轨迹，以收集新的数据输入仿真。我们在海星上的演示表明，适当使用可微模拟器中的梯度不仅缩小了模拟与现实的差距，而且在真实实验中提高了开环控制器的性能。
Underwater soft robots are challenging to model and control because of their high degrees of freedom and their intricate coupling with water. In this letter, we present a method that leverages the recent development in differentiable simulation coupled with a differentiable, analytical hydrodynamic model to assist with the modeling and control of an underwater soft robot. We apply this method to Starfish, a customized soft robot design that is easy to fabricate and intuitive to manipulate. Our method starts with data obtained from the real robot and alternates between simulation and experiments. Specifically, the simulation step uses gradients from a differentiable simulator to run system identification and trajectory optimization, and the experiment step executes the optimized trajectory on the robot to collect new data to be fed into simulation. Our demonstration on Starfish shows that proper usage of gradients from a differentiable simulator not only narrows down its simulation-to-reality gap but also improves the performance of an open-loop controller in real experiments.