Soft robots are interesting examples of hyper-redundancy in robotics. However, the nonlinear continuous dynamics of these robots and the use of hyper-elastic and visco-elastic materials make modeling these robots more complicated. This study presents a geometric inverse kinematics (IK) model for trajectory tracking of multi-segment extensible soft robots, where each segment of the soft actuator is geometrically approximated with a rigid links model to reduce the complexity. In this model, the links are connected with rotary and prismatic joints, which enable both the extension and rotation of the robot. Using optimization methods, the desired configuration variables of the soft actuator for the desired end-effector positions were obtained. Furthermore, the redundancy of the robot is applied for second task applications, such as tip angle control. The model’s performance was investigated through kinematics and dynamics simulations and numerical benchmarks on multisegment soft robots. The results showed lower computational costs and higher accuracy compared to most existing models. The method is easy to apply to multi-segment soft robots in both 2D and 3D, and it was experimentally validated on 3D-printed soft robotic manipulators. The results demonstrated the high accuracy in path following using this technique.
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