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Relevant bibliographies by topics / Autonomous robotic surgery

Academic literature on the topic 'Autonomous robotic surgery'

Author: Grafiati

Published: 11 March 2023

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Journal articles
Dissertations / Theses
Book chapters
Conference papers

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Journal articles on the topic "Autonomous robotic surgery"

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Abdelaal, Alaa Eldin, Jordan Liu, Nancy Hong, Gregory D. Hager, and Septimiu E. Salcudean. "Parallelism in Autonomous Robotic Surgery." IEEE Robotics and Automation Letters 6, no. 2 (April 2021): 1824–31. http://dx.doi.org/10.1109/lra.2021.3060402.

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Ray, Katrina. "Autonomous robotic laparoscopic gastrointestinal surgery." Nature Reviews Gastroenterology & Hepatology 19, no. 3 (February 1, 2022): 148. http://dx.doi.org/10.1038/s41575-022-00584-z.

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Yang, Shuo, Jiahao Chen, An Li, Ping Li, and Shulan Xu. "Autonomous Robotic Surgery for Immediately Loaded Implant-Supported Maxillary Full-Arch Prosthesis: A Case Report." Journal of Clinical Medicine 11, no. 21 (November 7, 2022): 6594. http://dx.doi.org/10.3390/jcm11216594.

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Robotic systems have emerged in dental implant surgery due to their accuracy. Autonomous robotic surgery may offer unprecedented advantages over conventional alternatives. This clinical protocol was used to show the feasibility of autonomous robotic surgery for immediately loaded implant-supported full-arch prostheses in the maxilla. This case report demonstrated the surgical protocol and outcomes in detail, highlighting the pros and cons of the autonomous robotic system. Within the limitations of this study, autonomous robotic surgery could be a feasible alternative to computer-assisted guided implant surgery.

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Rhatomy,MD, Sholahuddin, Krisna Yuarno Phatama, Asep Santoso, Kukuh Dwiputra Hernugrahanto, and Nicolaas Budhiparama. "Robot-Assisted in Hip and Knee Surgery: Are we ready?" Hip and Knee Journal 2, no. 2 (August 25, 2021): 54–56. http://dx.doi.org/10.46355/hipknee.v2i2.111.

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The word 'robot' is derived from the Polish word "robota," which means forced labor. It describes a machine that carries out various tasks either automatically or with minimal external input, especially one that is programmable. There are two main types of robotic surgery systems: haptic and autonomous. Haptic or tactile systems allow the surgeon to use or drive the robot to perform a surgical procedure. This technology requires constant input by the surgeon for the procedure to proceed. In contrast, autonomous robotic systems require the surgeon to perform the approach and set up the machine, but once engaged, the robot completes the surgery without the surgeon's help. The use of robotic technology has, in some cases, facilitated minimally invasive surgery, which has gained popularity with some patients. In spinal surgery, robotic technology has been successfully used to increase the accuracy of implant placement. Furthermore, robotic technology can improve the radiological alignment of implants following the pre-operative plan.1,2

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Shademan, Azad, Ryan S. Decker, Justin D. Opfermann, Simon Leonard, Axel Krieger, and Peter C. W. Kim. "Supervised autonomous robotic soft tissue surgery." Science Translational Medicine 8, no. 337 (May 4, 2016): 337ra64. http://dx.doi.org/10.1126/scitranslmed.aad9398.

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Rivas-Blanco, Irene, Carlos Perez-del-Pulgar, Carmen López-Casado, Enrique Bauzano, and Víctor Muñoz. "Transferring Know-How for an Autonomous Camera Robotic Assistant." Electronics 8, no. 2 (February 18, 2019): 224. http://dx.doi.org/10.3390/electronics8020224.

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Robotic platforms are taking their place in the operating room because they provide more stability and accuracy during surgery. Although most of these platforms are teleoperated, a lot of research is currently being carried out to design collaborative platforms. The objective is to reduce the surgeon workload through the automation of secondary or auxiliary tasks, which would benefit both surgeons and patients by facilitating the surgery and reducing the operation time. One of the most important secondary tasks is the endoscopic camera guidance, whose automation would allow the surgeon to be concentrated on handling the surgical instruments. This paper proposes a novel autonomous camera guidance approach for laparoscopic surgery. It is based on learning from demonstration (LfD), which has demonstrated its feasibility to transfer knowledge from humans to robots by means of multiple expert showings. The proposed approach has been validated using an experimental surgical robotic platform to perform peg transferring, a typical task that is used to train human skills in laparoscopic surgery. The results show that camera guidance can be easily trained by a surgeon for a particular task. Later, it can be autonomously reproduced in a similar way to one carried out by a human. Therefore, the results demonstrate that the use of learning from demonstration is a suitable method to perform autonomous camera guidance in collaborative surgical robotic platforms.

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Rodriguez y Baena, Ferdinando, and Brian Davies. "Robotic surgery: from autonomous systems to intelligent tools." Robotica 28, no. 2 (August 27, 2009): 163–70. http://dx.doi.org/10.1017/s0263574709990427.

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SUMMARYA brief history of robotic surgery is provided, which describes the transition from autonomous robots to hands-on systems that are under the direct control of the surgeon. An example of the latter is the Acrobot (for active-constraint robot) system used in orthopaedics, whilst soft-tissue surgery is illustrated by the daVinci telemanipulator system. Non-technological aspects of robotic surgery have often been a major impediment to their widespread clinical use. These are discussed in detail, together with the role of navigation systems, which are considered a major competitor to surgical robots. A detailed description is then given of a registration method for robots to achieve improved accuracy. Registration is a major source of error in robotic surgery, particularly in orthopaedics. The paper describes the design and clinical implementation of a novel method, coined the bounded registration method, applied to minimally invasive registration of the femur. Results of simulations which compare the performance of bounded registration with a standard implementation of the iterative closest point algorithm are also presented, alongside a description of their application in the Acrobot hands-on robot, used clinically for uni-condylar knee arthroplasty.

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Rosen, Jacob, and Ji Ma. "Autonomous Operation in Surgical Robotics." Mechanical Engineering 137, no. 09 (September 1, 2015): S15—S18. http://dx.doi.org/10.1115/1.2015-sep-9.

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The article focuses on developing an algorithm for automation based on stereo computer vision and dynamic registration in a surgical robotic context. The performance of the algorithm was further tested experimentally utilizing the block transfer task which corresponds to tissue manipulation as designed by Fundamentals of Laparoscopic Surgery (FLS). The surgical robotics field as a whole progresses towards the reduction of invasiveness limiting the trauma at the periphery of the surgical site and increase of semi-autonomous operation while positioning the surgeon as a decision maker rather than as an operator. The autonomous FLS task is implemented successfully and tested experimentally with the Raven II surgical robot system. The data indicate that the autonomous operational mode has better overall performance and limited tool-environment interaction compared with the human teleoperation mode. Surgeon’s intention may also be extracted from a database that may lead to seamless switching between the human operator and the autonomous system and in that sense, it may allow the autonomous algorithm to cope with more complex surgical environments.

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Bani, Mehrdad J. "Autonomous Camera Movement for Robotic-Assisted Surgery: A Survey." International Journal of Advanced Engineering, Management and Science 3, no. 8 (2017): 829–36. http://dx.doi.org/10.24001/ijaems.3.8.2.

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Prendergast, J. Micah, and Mark E. Rentschler. "Towards autonomous motion control in minimally invasive robotic surgery." Expert Review of Medical Devices 13, no. 8 (July 11, 2016): 741–48. http://dx.doi.org/10.1080/17434440.2016.1205482.

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Dissertations / Theses on the topic "Autonomous robotic surgery"

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Sneath, Evan B. "Artificial neural network training for semi-autonomous robotic surgery applications." University of Cincinnati / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1416231638.

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Sudhakaran, Nair Sudhesh. "A Virtual Framework for Semi-Autonomous Robotic Surgery using Real-Time Spatial Mapping." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1378196074.

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Tagliabue, Eleonora. "Patient-specific simulation for autonomous surgery." Doctoral thesis, 2022. http://hdl.handle.net/11562/1061936.

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An Autonomous Robotic Surgical System (ARSS) has to interact with the complex anatomical environment, which is deforming and whose properties are often uncertain. Within this context, an ARSS can benefit from the availability of patient-specific simulation of the anatomy. For example, simulation can provide a safe and controlled environment for the design, test and validation of the autonomous capabilities. Moreover, it can be used to generate large amounts of patient-specific data that can be exploited to learn models and/or tasks. The aim of this Thesis is to investigate the different ways in which simulation can support an ARSS and to propose solutions to favor its employability in robotic surgery. We first address all the phases needed to create such a simulation, from model choice in the pre-operative phase based on the available knowledge to its intra-operative update to compensate for inaccurate parametrization. We propose to rely on deep neural networks trained with synthetic data both to generate a patient-specific model and to design a strategy to update model parametrization starting directly from intra-operative sensor data. Afterwards, we test how simulation can assist the ARSS, both for task learning and during task execution. We show that simulation can be used to efficiently train approaches that require multiple interactions with the environment, compensating for the riskiness to acquire data from real surgical robotic systems. Finally, we propose a modular framework for autonomous surgery that includes deliberative functions to handle real anatomical environments with uncertain parameters. The integration of a personalized simulation proves fundamental both for optimal task planning and to enhance and monitor real execution. The contributions presented in this Thesis have the potential to introduce significant step changes in the development and actual performance of autonomous robotic surgical systems, making them closer to applicability to real clinical conditions.

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Dumpert, Jason James. "Towards supervised autonomous task completion using an in vivo surgical robot." 2009. http://proquest.umi.com/pqdweb?did=1902406691&sid=4&Fmt=2&clientId=14215&RQT=309&VName=PQD.

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Thesis (Ph.D.)--University of Nebraska-Lincoln, 2009.
Title from title screen (site viewed July 8, 2010). PDF text: xi, 200 p. : ill. (chiefly col.) ; 12 Mb. UMI publication number: AAT 3378560. Includes bibliographical references. Also available in microfilm and microfiche formats.

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Book chapters on the topic "Autonomous robotic surgery"

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Casals, Alícia. "Robots in surgery." In Autonomous Robotic Systems, 222–34. London: Springer London, 1998. http://dx.doi.org/10.1007/bfb0030808.

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Dolph, Erica, Crystal Krause, and Dmitry Oleynikov. "Future Robotic Systems: Microrobotics and Autonomous Robots." In Robotic-Assisted Minimally Invasive Surgery, 329–35. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96866-7_40.

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López, Alfonso Montellano, Mojtaba Khazravi, Robert Richardson, Abbas Dehghani, Rupesh Roshan, Tomasz Liskiewicz, Ardian Morina, David G. Jayne, and Anne Neville. "Locomotion Selection and Mechanical Design for a Mobile Intra-abdominal Adhesion-Reliant Robot for Minimally Invasive Surgery." In Towards Autonomous Robotic Systems, 173–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23232-9_16.

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Tzemanaki, Antonia, Sanja Dogramadzi, Tony Pipe, and Chris Melhuish. "Towards an Anthropomorphic Design of Minimally Invasive Instrumentation for Soft Tissue Robotic Surgery." In Advances in Autonomous Robotics, 455–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32527-4_56.

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Jörg, Stefan, Rainer Konietschke, and Julian Klodmann. "Classification of Modeling for Versatile Simulation Goals in Robotic Surgery." In Frontiers of Intelligent Autonomous Systems, 357–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35485-4_31.

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Sengül, Ali, Attila Barsi, David Ribeiro, and Hannes Bleuler. "Role of Holographic Displays and Stereovision Displays in Patient Safety and Robotic Surgery." In Frontiers of Intelligent Autonomous Systems, 369–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35485-4_32.

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Morandi, Angelica, Monica Verga, Elettra Oleari, Lorenza Gasperotti, and Paolo Fiorini. "A Methodological Framework for the Definition of Patient Safety Measures in Robotic Surgery: The Experience of SAFROS Project." In Frontiers of Intelligent Autonomous Systems, 381–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35485-4_33.

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Sandoval, Juan, Med Amine Laribi, and Saïd Zeghloul. "Autonomous Robot-Assistant Camera Holder for Minimally Invasive Surgery." In Robotics and Mechatronics, 465–72. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30036-4_42.

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Raczkowsky, Jörg, Philip Nicolai, Björn Hein, and Heinz Wörn. "System Concept for Collision-Free Robot Assisted Surgery Using Real-Time Sensing." In Frontiers of Intelligent Autonomous Systems, 391–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35485-4_34.

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Comparetto, Ciro, and Franco Borruto. "Applications of Robotics in Gynecological Surgery." In Design and Control Advances in Robotics, 256–94. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-5381-0.ch014.

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Robotic-assisted surgery is a branch of engineering that develops robotic machines that allow the operator to perform surgery by maneuvering, from a distance, a robot that is not completely autonomous but capable of performing controlled maneuvers. It is a technique that has recently come into use, even in selected centers, and represents a further step in the field of minimally invasive surgery (MIS). It has basically the same indications, but, at the moment, it is reserved for selected patients. Compared to traditional video-assisted surgery, it has some important differences. The surgeon is physically distant from the operating field and sits at a console, equipped with a monitor, from which, through a complex system, he controls the movement of the robotic arms. To these are fixed the various surgical tools—forceps, scissors, dissectors—which a team present at the operating table introduces into the cavity where the surgery is performed.

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Conference papers on the topic "Autonomous robotic surgery"

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Fiorini, P., D. Dall Alba, M. Ginesi, B. Maris, D. Meli, H. Nakawala, and A. Roberti. "Challenges of Autonomous Robotic Surgery." In The Hamlyn Symposium on Medical Robotics. The Hamlyn Centre, Faculty of Engineering, Imperial College London, 2019. http://dx.doi.org/10.31256/hsmr2019.53.

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Francom, Matthew, Clinton Burns, Philip Repisky, Benjamin Medina, Alex Kinney, Erick Tello, and Pinhas Ben-Tzvi. "Development of Autonomous Robotic Cataract Surgery Device." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59643.

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The current rate of incidence of cataracts is increasing faster than treatment capacity, and an autonomous robotic system is proposed to mitigate this by carrying out cataract surgeries. The robot is composed of a three actuator RPS parallel mechanism in series with an actuated rail mounted roller that moves around the eye, and is designed to perform a simplified version of the extracapsular cataract surgery procedure autonomously. The majority of the design work has been completed, and it is projected that the system will have a tool accuracy of 0.167 mm, 0.141 mm, and 0.290 mm in the x, y, and z directions, respectively. Such accuracies are within the acceptable errors of 1.77mm in the x and y directions of the horizontal plane, as well as 1.139 mm in the vertical z direction. Tracking of the tool when moving at 2 mm/s should give increments of 0.08 mm per frame, ensuring constant visual feedback. Future work will involve completing construction and testing of the device, as well as adding the capability to perform a more comprehensive surgical procedure if time allows.

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Sneath, Evan, Christopher Korte, and Grant Schaffner. "Semi-Autonomous Robotic Surgery for Space Exploration Missions." In AIAA Scitech 2020 Forum. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2020. http://dx.doi.org/10.2514/6.2020-1379.

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Connolly, Laura, Anton Deguet, Kyle Sunderland, Andras Lasso, Tamas Ungi, John F. Rudan, Russell H. Taylor, Parvin Mousavi, and Gabor Fichtinger. "An Open-Source Platform for Cooperative, Semi-Autonomous Robotic Surgery." In 2021 IEEE International Conference on Autonomous Systems (ICAS). IEEE, 2021. http://dx.doi.org/10.1109/icas49788.2021.9551149.

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Ginesi, Michele, Daniele Meli, Andrea Roberti, Nicola Sansonetto, and Paolo Fiorini. "Autonomous task planning and situation awareness in robotic surgery." In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020. http://dx.doi.org/10.1109/iros45743.2020.9341382.

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Col, Tommaso Da, Andrea Mariani, Anton Deguet, Arianna Menciassi, Peter Kazanzides, and Elena De Momi. "SCAN: System for Camera Autonomous Navigation in Robotic-Assisted Surgery." In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2020. http://dx.doi.org/10.1109/iros45743.2020.9341548.

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Le, Hanh N. D., Justin D. Opfermann, Michael Kam, Sudarshan Raghunathan, Hamed Saeidi, Simon Leonard, Jin U. Kang, and Axel Krieger. "Semi-Autonomous Laparoscopic Robotic Electro-Surgery with a Novel 3D Endoscope." In 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. http://dx.doi.org/10.1109/icra.2018.8461060.

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Nguyen, Ngoc Duy, Thanh Nguyen, Saeid Nahavandi, Asim Bhatti, and Glenn Guest. "Manipulating Soft Tissues by Deep Reinforcement Learning for Autonomous Robotic Surgery." In 2019 IEEE International Systems Conference (SysCon). IEEE, 2019. http://dx.doi.org/10.1109/syscon.2019.8836924.

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Sophia, Strasser, and Kucera Markus. "Artificial intelligence in safety-relevant embedded systems - on autonomous robotic surgery." In 2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI). IEEE, 2021. http://dx.doi.org/10.1109/iiai-aai53430.2021.00089.

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Tagliabue, Eleonora, Daniele Meli, Diego Dall'Alba, and Paolo Fiorini. "Deliberation in autonomous robotic surgery: a framework for handling anatomical uncertainty." In 2022 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2022. http://dx.doi.org/10.1109/icra46639.2022.9811820.

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