1 introduction
The development of intelligent endorobots transforms the field of mini-invasive procedures by introducing new solutions for diagnosis and treatment within the human body. These advanced robotic systems allow increased maneuverability, improved precision and greater patient safety. Clinicians are increasingly supported by endorobots to make the diagnosis and treatment of organs that are difficult to reach with small incisions or natural orifices. New technologies have provided a tool to improve the design of these devices (for example, reduce size, improve dexterity and reduce stress and fatigue), while AI and ML algorithms provide a tool to support clinical judgment (Manfredi, 2021; Manfredi, 2022).
This new generation of endorobots is not only capable of imitating user movements, but also of performing tasks at different levels of autonomy. Their design requires a multidisciplinary team that involves experts in various areas of research, including actuators, sensors, control, mechanics, artificial intelligence (AI) and automatic learning (ML) and imagery. The increase in the level of autonomy introduces ethical concerns concerning responsibility, regulatory compliance and safety while avoiding the limits of technological progress.
The design of endorobots for endoluminal applications requires a multidisciplinary approach covering different research aspects. The objective of this research subject was to collect contributions from various disciplines, offering readers a complete overview of the field.
2 Research subject content
This research subject includes a collection of articles and criticisms which can be summarized in three main themes: i) Navigation, II) Robotics and III) control and IA. These themes include critical progress of technologies, taking up challenges in handling, automation and medical decision -making.
2.1 Navigation
One of the critical challenges of endoluminal robotics is navigation through complex anatomical tracks (Berthet-Rayne and & Yang) Introduce a minimal occupation volume (displacement) A teleoperation method extending the following navigation concept. This approach optimizes the use of the available space surrounding the robot while guaranteeing a safe and effective movement through tortuous environments. Unlike traditional navigation methods, displacement offers flexibility and adaptability, addressing constraints such as joint limitations and kinematic complexities. The proposed method was validated by simulations and control experiences, demonstrating its application potential in flexible endoscopic surgery.
2.2 Robotics
Robotic solutions for endoluminal procedures progress towards increased modularity, reusability and better adaptability. (Lensen et al.) presented Misli-Drive, a modular sterilizable robotic conductor for adjustable laparoscopic instruments, illustrates these developments. This robotic pilot is of key challenges in instrument control, sterilization and user adaptability. It incorporates a rapidly released instrument clutch mechanism and integrated sensors for real -time feedback. Compared to existing robotic systems, the Misli-Drive Dissive demonstrates an effective exchange of instruments and reduced cleaning complexity, making it a viable solution for sustainable robotics surgery.
Another contribution is the study on gentle robotics and tactile detection for tissue palpation using electrical impedance tomography (EIT) (EIT)Alian et al.). This research incorporates soft robotics into EIT -based tactile detection to allow a real -time assessment of tissue rigidity, improving the capacities of flexible endoscopic robots. The results indicate that soft continuum robots with integrated touch sensors can improve cancer diagnostics at an early stage, providing a non -invasive means of classifying tissue abnormalities.
2.3 Control and AI
The integration of AI and control strategies is revolutionizing endorobotic systems. A complete review on control strategies based on models and without models for soft actuators in colonoscopy deals with different control approaches to improve robotic maneuverability (Asgari et al.). The study highlights the importance of adaptive control strategies which can optimize gentle robotic movements while minimizing the force exerted on the colic wall. By taking advantage of the IA and sensors feedback loops, these control mechanisms can improve the safety and efficiency of endoscopic procedures.
Another contribution to this theme is research on the estimation of self-supervised monocular depth for high field of vision colonoscopy cameras (Mathew et al.). This study presents an AI-based method to estimate the depth in colonoscopy images using a self-supervised learning approach. The method improves robotic navigation by providing a real -time 3D spatial consciousness, by reporting challenges linked to occlusions, low -texture surfaces and high optical distortion in colonoscopy cameras with wide angle. The integration of these depth estimation models focused on AI is promising to improve the accuracy and safety of the robot assisted colonoscopy.
Another article of this research subject explores AI applications in the diagnosis and classification of inflammatory intestine (Mii) diseases (Mii)Braverman-Jaiven and and Manfredi). The study highlights the potential of in -depth learning algorithms and convolutional neural networks (CNN) in the automation of polyps detection and the classification of MII. Although the diagnoses led by AI have shown promising results, the study highlights the need for larger annotated data games and more robust validation to improve reliability and clinical applicability.
3 Conclusion
Manuscripts published in this research subject have significant progress in intelligent endorobots for endoluminal procedures, navigation covering navigation, robotics and AI control. Contributions highlight the potential of gentle robotics, modular robotic drivers and IA -improved control systems to improve surgical accuracy, reduce patient discomfort and improve diagnostic capacities. However, challenges remain, in particular the need for regulatory executives, integration with existing clinical workflows and additional validation through clinical trials. Future research should focus on refining these technologies to allow generalized adoption in mini-invasive surgery and diagnostic interventions.
The integration of intelligent robotic solutions into endoluminal procedures marks a paradigm shift in the field of medical robotics. By approaching the current limits and by exploiting the capacities of AI, sweet robotics and advanced control systems, the future of mini-invasive interventions should become more precise, efficient and focused on the patient.
Contributions from authors
LM: conceptualization, writing-project writing, writing and publishing. JS -M: Writing – Revision and edition. HW: Writing – Revision and edition. AM: Writing – Revision and edition.
Funding
The authors declare that no financial support has been received for the research and / or publication of this article.
Thanks
The associated publishers invited to this research subject wish to express their gratitude to Professor Kostas J. Kyriakopoulos, editor -in -chief of the frontier field in Robotics and IA, for the opportunity to publish this subject of research. We greatly appreciate the responsiveness of the editor -in -chief of specialties, associated publishers and staff members on opportune support throughout the examination and publication processes. We also express our sincere gratitude to the many examiners who have contributed to this research subject with their time and their expertise.
Conflict of interest
The authors declare that research has been carried out in the absence of commercial or financial relations which could be interpreted as a potential conflict of interest.
The author (s) said that they were a member of the border editorial committee at the time of submission. This had no impact on the peer examination process and the final decision.
Generative declaration of AI
The authors declare that no generative was used in the creation of this manuscript.
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