Adaptive Visual Servoing for an Underwater Soft Robot Considering Refraction Effects

Robots inspired from marine organisms are tremendously developed for applications of underwater exploration, rescuing, navigation, etc. In this article, we implement an uncalibrated visual servoing scheme to achieve accurate positioning performance of an octopus-tentacle-like soft robot arm. The image-based adaptive visual servoing controller is designed based on the underwater dynamic model of the robot system. An adaptive mechanism to solve the tedious camera calibration problem is also extremely complicated in underwater environment due to the refraction effect resulting in changes of optical condition. In this article, this effect is analogous to the radial distortion. The presented algorithm can linearize the distortion model, and then online iteratively estimate the unknown image mapping model based on the classical Slotine-Li adaptive algorithm. The intrinsic and extrinsic parameters can also be estimated in real time. The presented adaptive controller is verified both theoretically using the Lyapunov stability analysis to prove the stability of the dynamical system, and experimentally to prove the accuracy and rapid convergence to the target image position.