Inverse kinematics is fundamental and useful for soft robots. Using this capability, one could realize the coordinate-based control and point-to-point movement of the soft manipulator. Inverse kinematics is also critical for picking and placing tasks, as well as trajectory planning and obstacle avoidance. Further, the quick solution of inverse kinematics also helps to improve the real-time control ability of soft manipulators. However, the inverse kinematics problem can become very complicated due to the hyper redundancy of soft robots. Much of the inverse kinematics problem of a robotic system depends on the modeling implemented for the forward kinematics of that robot. Nevertheless, the large group’s nonlinear equations in the robot’s equations can cause the huge complexity of the inverse solution.
There could be different approaches towards solving the inverse kinematics of soft robots depending on the model used for the forward kinematics of the robot. In this project we use a piecewise constant curvature (PCC) model to find feasible paths between given start and goal configurations of a soft robot.