Validation of a Pseudo-Data-Generation-Software for FBG-Optical Fiber Based Shape Sensing

Shape sensing based on FBG-optical fibers is a current research topic of several working groups worldwide. The sensor is integrated into flexible snakelike objects such as e.g. endoscopes or flexible tubes to detect shape deformation. This way, the objects can be observed and tracked. Shapesensing supports navigation of flexible instruments. Currently, robotic systems consist of ridgit joints only. Shapesensing provides the required information for automated control of the robot end-effector position and orientation in case additional flexible joints are integrated into the robotic system. In this field of research, some fundamental aspects have already been researched and standard algorithms are published. As the sensor technology is supposed to be used in medical technology, the requirements towards the sensor accuracy and robustness are demanding. Therefor, shapesensing still needs to be improved. At the Institute for Anthropomatics and Robotics Intelligent Process Control and Robotics - Karlsruhe Institute of Technology (IAR-IPR-KIT), fundamentally new sensor concepts are investigated. However, the testing of new algorithms and sensor designs is very costly as a high number of prototypes has to be build. To avoid these costs in time and money, the tests are planned based on pseudo measurement data. To efficiently generate this kind of data, we developed a software. In this paper, the individual parts of the software are presented and the main functionality and easy-of-use are evaluated.