Dynamic Control of Soft Continuum Manipulators
Adaptive Dynamic Sliding Mode Control of Soft Continuum Manipulators
Soft robots are made of compliant materials and perform tasks that are challenging for rigid robots. However, their continuum nature makes it difficult to develop model-based control strategies. In practice, it's hard to have a complete model with all the parameters precisely identified. In addition, the dynamic parameters may change when the robot operates in an unstructured environment. This work presents a robust model-based control scheme for soft continuum robots. Our dynamic model is based on the Euler-Lagrange approach. In our model, we use an accurate description of the robot's inertia rather than oversimplifying assumptions. Using this model, we develop an adaptive sliding mode control scheme that is robust against model parameter uncertainties and unknown input disturbances. With a physical soft continuum arm, we evaluate the effectiveness of our controller in tracking task-space trajectory under different payloads. Our controller achieves tracking performance up to 38% better than a state-of-the-art controller, i.e., the inverse dynamics method. This model-based control design is also flexible and can be generalized to any continuum robotic arm with an arbitrary number of segments. Our adaptive control strategy enables soft continuum robotic arms to be used in real-world applications, such as picking up and placing unknown mass objects.
Dynamic Task Space Control Enables Soft Manipulators to Perform Real-World Tasks
Dynamic motions are a key feature of robotic arms, enabling them to perform tasks quickly and efficiently. A majority of real-world soft robots rely on a quasistatic control approach, without taking dynamic characteristics into consideration. As a result, robots with this restriction move slowly and are not able to adequately deal with forces, such as handling unexpected perturbations or manipulating objects. A dynamic approach to control and modeling would allow soft robots to move faster and handle external forces more efficiently. In previous studies, different aspects of modeling, dynamic control, and physical implementation have been examined separately, while their combination has yet to be thoroughly investigated. Herein, the accuracy of the dynamic model of the multisegment continuum robot is improved by adding new elements that include variable stiffness and actuation behavior. Then, this improved model is integrated with state-of-the-art system identification and dynamic task space control and experiments are performed to validate this combination on a real-world manipulator. As a means of encouraging future research on dynamic control for soft robotic manipulators, the source code is made available for modeling, control, and system identification, along with the recipes for fabricating the manipulator.