As the Natural Orifice Transluminal Endoscopic Surgery (NOTES) operations using a robotic endoscope includes a change of path due to movement of organs and other body parts, it is assumed that the endoscopic robot will benefit from on-line path planning.
It has been mentioned that trajectory planning is needed when the robot has to move and react fast in its environment (Shiller, 2015). However, when regarding a robotic application such as the endoscope, the implementation of path planning will suffice, as the endoscope does not have to cope with high speeds or fast interacting environments.
One of the techniques that already is proposed in endoscopic continuum robots (Gayle et al., 2005) makes use of a motion planner that computes an estimated path that is furthest from all near obstacles and also resolves any collisions using a non-penetration constraint. (Gayle et al., 2005) In more detail, the article proposes an overlap algorithm to check whether colli- sions occur, together with an initial path based on a probabilistic roadmap planner and the approximate medial axis of the work space. The goal of the authors was to generate a collision- free path, while minimizing the energy used. To check for overlap, they used 2.5D overlap tests. Two experiments were performed in simulation, containing path planning of a spherical robot through walls and the simulation of catheters in liver chemoembolization. (Gayle et al., 2005) The article of Chen et al. (Chen et al., 2014) provides some interesting path planning algorithms as well. In the article two techniques are mentioned; uncoiling path planning and follow-the- leader path planning. The first one provides a way to insert the endoscope without needing to use any extra actuator, whereas the latter approach helps in automatically steering the other segments of the continuum robot after the movements of the tip that have been performed. (Chen et al., 2014)
As mentioned earlier, the use of lumen centralization and visual odometry are visual-based planning techniques with lots of potential in terms of steering the endoscope (van der Stap et al., 2013) (Khan and Gillies, 1996). However, according to van der Stap et al. (van der Stap et al., 2013), no experiments in vivo have been executed.
A.9 Discussion
This review has covered several approaches developed throughout the history of path plan- ning, as well as alternative movement methods. However, from this research it is still difficult to determine which approach would be most suitable for application in endoscopic feedback during operation. Essential information regarding performance, advantages and disadvant- ages is currently missing in this research. Future approach should consider a more elaborately drawn image of all techniques in a overview table. Furthermore, some recent developments in terms of algorithms should be included in the research.
Further ideas for future research include the further investigation of virtual endoscopy, a topic which has been more widely addressed in literature. Virtual endoscopy can be used to train and to pre-plan possible trajectories for operation, taking visual effort away from navigation during operation (Paik et al., 1998). Articles regarding virtual endoscopy also introduce new approaches that could be of interest for eventual application of path planning-based feedback during operation. This collection of information can be very insightful for determining the future target of this research.
A.10 Conclusion
An important aspect of robotics is path planning. Path planning consists of a starting point and an end goal, to which a path is drawn while evading potential obstacles along the way and taking possible performance criteria into consideration. These criteria can range from energy used, to time spent, but can also consider robot-specific boundaries regarding motion or other characteristics.
This research addressed several path planning algorithms and made a distinction between on- line and off-line approaches, of which on-line is based on dynamic environments and having to react to moving obstacles, whereas off-line approaches mainly address the paths that are pre-defined in a stationary non-changing environment. Furthermore, the concept of traject- ory planning is introduced. Most attention was spend on types of algorithms suitable for endo- scopic purposes, which was why new developments in on-line path planning approaches were highlighted.
Next to these approaches, some alternative approaches to path planning were mentioned. One of the outstanding methods was the use of lumen centralization and visual odometry to steer the endoscope in the correct direction.
Approaches in virtual endoscopy are also studied, of which some researches proposed inter- esting approaches to path planning. Path planning in virtual endoscopy mainly relies on the use of line centralization, which basically implies generating points that are furthest away from the walls, interconnected to create a path. This is quite similar to the approach of Voronoi dia- grams. The article of Merritt et al. (Merritt et al., 2007) provides a novel approach in interfacing the planned path as visual feedback for the surgeon to use during operation.
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Appendix B: Commercial Endoscopes
The current commercial endoscopes vary in terms of dimensions and other characteristics, such as bending capability and tooling options. Depending on the application, other aspects are of course of importance. Table 1 contains the data of several commercial endoscopes, which have been found in several brochures of commercial companies. It has been chosen to display only the biggest diameter in the endoscope, as sometimes the tip might be bigger than the overall diameter and vice versa. Furthermore, for the sake of overview, only the range per type of endoscope is shown.
Other sources were also investigated, but no clear information regarding flexible endoscopes for medical purposes were found in those sources. Other considered companies were looked at were Boston Scientific, Medtronic, Ethicon, Hologic, Comeg, B.Braun and Bayer.
Endoscope type Source d (mm) Bending angle (degrees) Remarks Bronchoscopy (Olympus, 2018/2019) 3.1-6.2 U:180-210/D:130/L:120/R:120
(Olympus, 2018/2019) 2.2-6 U:180/D:130/L:¬/R:¬
(Ambu, 2019) 4.2-6.2 U:130-180/D:110-180/L:¬/R:¬
Colonoscopy (Fujifilm, 2019) 11.1-12.8 U:180/D:180/L:160/R:160 (Fujifilm, 2019) 10.5 U:210/D:160/L:160/R:160 (Olympus, 2018/2019) 9.5-14.8 U:180/D:180/L:160/R:160
(Ambu, 2019) 18 U:180/D:180/L:180/R:180
Duoendoscopy (Fujifilm, 2019) 13.1 U:120/D:90/L:90/R:110
(Olympus, 2018/2019) 12.8 U:120/D:90/L:90/R:110 Enteroscopy (Fujifilm, 2019) 7.7-9.4 U:180/D:180/L:160/R:160
(Olympus, 2018/2019) 9.2 U:180/D:180/L:180/R:180 Gastroscopy (Fujifilm, 2019) 5.1-10.8 U:210/D:90/L:100/R:100
(Fujifilm, 2019) 9.8 U:210/D:120/L:100/R:100
(Olympus, 2018/2019) 5.8-12.9 U:210/D:90/L:100/R:100 Cystoscopy & (Olympus, 2018/2019) 2.7-5.5 U:210-220/D:120-130/L:¬/R:¬
Uteroscopy (Coloplast, 2019) U:80/D:90/L:¬/R:¬ dunclear
(Olympus, 2018/2019) 2.65-3.3 U:180-275/D:275/L:¬/R:¬
Laparascopy (Olympus, 2018/2019) 5.4 -10 U:100/D:100/L:100/ R:100 Rhinolaryngoscopy (Olympus, 2018/2019) 2.2-5.0 U:130/D:130/L:¬/R:¬
(Ambu, 2019) 3.5-5.5 U:130/D:130/L:¬/R:¬
(Olympus, 2018/2019) 2.65-3.3 U:180-275/D:275/L:¬/R:¬
Sigmoidoscopy (Fujifilm, 2019) 12.8 U:180/D:180/L:160/R:160
Choledochoscope (Olympus, 2018/2019) 5.2 U:160/D:130/L:¬/R:¬
Pleuroscope (Olympus, 2018/2019) 7 U:160/D:130/L:¬/R:¬
GI Fiberoscope (Olympus, 2018/2019) 9.8-13.8 U: 160-210/D: 90-180/ L:100-160/R: 100-160
Tracheal Intubation (Olympus, 2018/2019) 2.2 -5.2 U:120-180/D:120-130/L:¬/R:¬
Hysteroscope (Olympus, 2018/2019) 3.1 U:100/D:100/L:¬/R:¬
ENT Scope (Medtronic, 2016) 3.2-3.8 120-160 U:125/D:125/L:¬/R:¬ lbend=25 mm Table 1:Inventory of commercial endoscopes. As diameter- and bending angle columns suggest, this
information is a summary of even more commercial endoscopes. For the sake of overview, these endo-
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Appendix C: Fabrication process
The modules used for the creation of the complete endoscope have been fabricated in house, using the various types of EcoFlex and Dragon Skin that have been present at the research group. This section will concern the fabrication process, explaining the steps taken during this procedure. It will mainly focus on the fabrication process of the EcoFlex 0030 modules, as these are mainly used throughout the experiments. First, a quick recap is given concerning the design of the most frequently used modules, after which their fabrication process is high- lighted. Most of the fabrication process has been pioneered by Jan Lenssen (Lenssen, 2019), after which several adjustments have been made.
C.1 Design description
The EcoFlex 0030 modules consist mainly out of EcoFlex 0030 material, using EcoFlex 0050 for the chambers and Dragon Skin 10 for the lid of the module. The reason for having EcoFlex 0050 chambers is to increase the strength of the chambers, hopefully lasting longer during the process. The Dragon Skin 10 lid is used as an extra strong barrier to contain the expansion with, as the most pressure would be exerted in upwards direction.