Image-Based Online Command Adaptation and Guidance to Arbitrarily Shaped Objects for Robot-Assisted Medical Procedures

Abstract

Imaging techniques are established aids in surgical procedures and have become indispensable in modern medicine. Combined with robot-assisted systems, significantly higher precision can already be achieved today and work steps can be simplified. We hypothesize that algorithms can make the operations of the future safer and easier. The paper introduces an approach for the control of a robotic manipulator that, based on standardized imaging techniques, monitors and adapts externally given movement commands. The physician controls the system, benefits from the robot’s precision, and movements will be intervened in if unwanted contact with the environment would occur. This is important, e.g., when operating near sensitive tissue, nerves or bone that must not be injured. Objects from the image data are considered in the control scheme and may have arbitrary shape and size. Furthermore, since the approach can be in principle adapted to any shape it is shown how robot operations in confined spaces, that are challenging to achieve using an external controller, can be simplified by the introduced approach. The online evaluation takes place in Cartesian space and is then transformed into joint space using the inverse kinematics. The approach is implemented using GAZEBO and a simulation study is performed for the 6-DOF industrial manipulator Stäubli TX2-60.