Kinematic Modeling of Continuum Robots Using Artificial Intelligence Tools

Abstract

Continuum robots are progressively dwarfing traditional rigid robots in many areas, due to their outstanding flexibility and easy adaptation to almost any kind of trajectory, yet their kinematic modeling is presented as a drawback, in particular with multi-sections and variable curvature, which curbs the full benefit of these robots. In this context, this chapter presents the description of continuum robots and their kinematic modeling in detail. Firstly, the description of the behavior and forward kinematic models are presented for continuum robots with constant and variable curvatures. Then, to calculate the inverse kinematic model of continuum robots, artificial neural networks, and metaheuristic optimization techniques have been used to obtain the inverse kinematic model of single and multi-section continuum robots, respectively. To validate the utility of the proposed techniques, different trajectories are considered to be followed by considered robots. It is found that the developed techniques are powerful tools to deal with the high complexity of nonlinear equations, in particular when it comes to solving the inverse kinematic model of multi-section continuum robots with variable curvature. To have a closer look at the efficiency of the developed techniques during the follow-up of the proposed trajectories, 3D simulations have been carried out with different configurations.