In endoscopic minimally invasive surgery (MIS), it is desirable to be able to combine flexible mobility with enough stability to perform manipulations [1]. This lead to the development of soft robotics applications, such as the STIFF-FLOP manipulator [1]. The Robotics and Mechatronics group of the University of Twente developed their own soft robotic endoscope, which was named the MOLLUSC (Multi-LeveL Stiffness Controllable) and inspired by the STIFF-FLOP.
In many of the endoscopic operations, the region of target is not close to the insertion site. To access the target, therefore, the endoscope needs to pass through or around different deformable (soft tissues) or hard tissues. As a result, the accuracy and patient safety can be affected if the path the endoscope should be controlled through is not well-described in advance. Moreover, the current soft robotic endoscope might suffer from speed limitations during operation, due to delayed response of the module upon actuation.
In order to minimize the invasiveness during any endoscopic operation, the path from the insertion site to the target needs to be determined in a way that the target is reached with a reasonable speed, with the least dissection required and the least risk of damage to the tissues around the endoscope.
Previously, different approaches were found that implemented visual (virtual) feedback of the desired path towards the target region [2][3]. This was found to increase the speed of which the surgeon reached the target region [2]. Using visual feedback of the desired trajectory might thus increase the speed of the procedure of our soft robotic endoscope. As one of the key requirements of endoscopy and medical operations in general is safety, several safety conditions have to be incorporated as well. A path planning algorithm will be developed, which takes into account safety measures regarding pressure, maximum bending and stability, just as well as general constraints of the soft robotic endoscope.
The research question will be as follows:
How can we optimize reaching the target with our soft robotic endoscope using a modified path planning algorithm in a virtual endoscopic environment while considering the following aspects:
- safety and
- physical boundaries of the soft robotic endoscope?
References
[1] Cianchetti, M., & Menciassi, A. (2017). Soft robots in surgery. In Soft Robotics: Trends, Applications and Challenges (pp. 75-85). Springer, Cham.
[2] Wang, J., Ohya, T., Liao, H., Sakuma, I., Wang, T., Tohnai, I., & Iwai, T. (2011). Intravascular catheter navigation using path planning and virtual visual feedback for oral cancer treatment. The International Journal of Medical Robotics and Computer Assisted Surgery, 7(2), 214-224.
[3] Merritt, S. A., Rai, L., Gibbs, J. D., Yu, K. C., & Higgins, W. E. (2007, March). Method for continuous guidance of endoscopy. In Medical imaging 2007: physiology, function, and structure from medical images (Vol. 6511, p. 65110O). International Society for Optics and Photonics.