Modal-based Kinematics and Contact Detection of Soft Robots
This work addresses contact detection for soft robot modeling and control, which is incremental as it builds on existing methods for a specific actuator type.
The paper tackled the problem of contact detection and position estimation in soft robots by modeling a 1-DoF soft pneumatic actuator using a modal method and fixed centrode deviation, with simulation results showing accurate contact location estimation through nonlinear least squares optimization.
Soft robots offer an alternative approach to manipulate inside the constrained space while maintaining the safe interaction with the external environment. Due to its adaptable compliance characteristic, external contact force can easily deform the robot shapes and lead to undesired robot kinematic and dynamic properties. Accurate contact detection and contact position estimation are of critical importance for soft robot modeling, control, trajectory planning, and eventually affect the success of task completion. In this paper, we focus on the study of 1-DoF soft pneumatic bellow bending actuator, which is one of the fundamental components to construct complex, multi-DoF soft robots. This 1-DoF soft robot is modeled through the integral representation of the spacial curve. The direct and instantaneous kinematics are calculated explicitly through a modal method. The fixed centrode deviation (FCD) method is used to to detect the external contact and estimate contact location. Simulation results indicate that the contact location can be accurately estimated by solving a nonlinear least square optimization problem.