Augmented reality (AR) for surgical robotic and autonomous systems: State of the art, challenges, and solutions

Journal article

Seetohul, J,, Shafiee, M. and Sirlantzis, K. 2023. Augmented reality (AR) for surgical robotic and autonomous systems: State of the art, challenges, and solutions. Sensors. 23 (13), p. 6202. https://doi.org/10.3390/s23136202
AuthorsSeetohul, J,, Shafiee, M. and Sirlantzis, K.
AbstractDespite the substantial progress achieved in the development and integration of augmented reality (AR) in surgical robotic and autonomous systems (RAS), the center of focus in most devices remains on improving end-effector dexterity and precision, as well as improved access to minimally invasive surgeries. This paper aims to provide a systematic review of different types of state-of-the-art surgical robotic platforms while identifying areas for technological improvement. We associate specific control features, such as haptic feedback, sensory stimuli, and human-robot collaboration, with AR technology to perform complex surgical interventions for increased user perception of the augmented world. Current researchers in the field have, for long, faced innumerable issues with low accuracy in tool placement around complex trajectories, pose estimation, and difficulty in depth perception during two-dimensional medical imaging. A number of robots described in this review, such as Novarad and SpineAssist, are analyzed in terms of their hardware features, computer vision systems (such as deep learning algorithms), and the clinical relevance of the literature. We attempt to outline the shortcomings in current optimization algorithms for surgical robots (such as YOLO and LTSM) whilst providing mitigating solutions to internal tool-to-organ collision detection and image reconstruction. The accuracy of results in robot end-effector collisions and reduced occlusion remain promising within the scope of our research, validating the propositions made for the surgical clearance of ever-expanding AR technology in the future.
KeywordsAugmented reality (AR); Navigation; Robotic and autonomous systems (RAS); Surgery; Planning; Machine learning (ML); Robotic Surgical Procedures - methods
Year2023
JournalSensors
Journal citation23 (13), p. 6202
PublisherMDPI
ISSN1424-8220
Digital Object Identifier (DOI)https://doi.org/10.3390/s23136202
https://doi.org/s23136202
Official URLhttps://www.mdpi.com/1424-8220/23/13/6202
FunderEngineering and Physical Sciences Research Council
Publication dates
Online06 Jul 2023
Publication process dates
Accepted03 Jul 2023
Deposited04 Dec 2023
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File Access Level
Open
Output statusPublished
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