A Reliable Algorithm for Obtaining All-Inclusive Inverse Kinematics' Solutions and Redundancy Resolution of Continuum Robots

This paper presents a reliable algorithm for solving the inverse kinematic (IK) problem of continuum robots. Admittedly, there are an infinite number of configurations to get the robot's end point (EP) pose. Therefore, the proposed algorithm introduces a new solution that helps narrow the infinite number of the IK solutions down to a finite one by taking into account the first (n - 1) sections' sets of reachable EP poses, which are selected and created one-by-one from the first to (n - 1)th section, in which the Particle Swarm Optimization method is adopted to randomly pick up the first IK solution. However, a specific criterion has been accorded to select the appropriate IK solution (i.e., redundancy resolution) among the existing varieties that perfectly fits within the targeted trajectory. Furthermore, numerical experiments are performed on a Cable-Driven Continuum Robot for tracking a trajectory in a free and confined environment, pointing up on IK, multiple IK solutions and redundancy resolution. The obtained results demonstrated that the proposed algorithm is computationally accurate and efficient in obtaining all-inclusive IK solutions and redundancy resolution of continuum robots in comparison to previously proposed approaches. It is noteworthy to say that the proposed algorithm can be applied to any kind of continuum robots and most importantly regardless of its number of sections, which makes the developed algorithm a sovereign remedy for the IK problem of these robots.