Robotic Guidance Research Articles

Practice Pattern Variations in the Use of Neuromonitoring, Image Guidance, and Robotics for Lumbar Pedicle Screw Placement Based on a Nationwide Neurosurgery Survey

Lumbar pedicle screw placement surgery involves various assistive technologies, including fluoroscopic, stereotactic, or robotic navigation and intraoperative neuromonitoring (IONM). We aimed to discern neurosurgeons' preferences for screw placement techniques and IONM utility, while also considering the influence of experience. A survey was distributed to members of the Congress of Neurological Surgeons using REDCap software, collecting demographic data and querying preferred techniques for screw placement and IONM modalities. Opinions on IONM use during stereotactic or robotic navigation were also obtained. Responses were analyzed using Pearson's Chi Square and ANOVA tests via R software. Of 188 responses, 35.5% (n=67) reported 1-10 years of experience and 64.5% (n=121) reported ≥11 years. Less experienced neurosurgeons utilized stereotactic navigation more than those with greater experience (p < 0.001). Seasoned neurosurgeons utilized fluoroscopic guidance more often (p = 0.038). Less experienced neurosurgeons employed 1.69 (±0.11) techniques for their fixation surgeries compared to 1.50 (±0.0.8) for more experienced neurosurgeons. Robotic navigation utilization was low and comparable between the groups. Surgeons employing multiple techniques utilized t-EMG the most (62.1%, p = 0.024). No strong opinions emerged on the necessity of multi-modality IONM with robotic or stereotactic navigation. This national survey shows that stereotactic navigation is the predominant technique for pedicle screw placement among less experienced neurosurgeons, with seasoned neurosurgeons leaning towards fluoroscopic guidance. Robotic guidance was the least utilized technique with no observed difference based on experience. Neurosurgeons employing multiple techniques use IONM the most, compared with surgeons who only use stereotactic navigation and/or robotic guidance.

Mathematical modelling of a flexible steering robot for vehicle trajectory control

Abstract This paper presents a mathematical modelling framework for a novel design of a steering robot to control vehicle trajectory. A systematic approach is adopted to capture the dynamics of a belt transmission mechanical system of the robot. The steering robot is powered by a Brushless Direct Current (BLDC) servo motor which employs a Field Oriented Current (FOC) control for motor position control. The system’s accuracy is demonstrated through simulations conducted using MATLAB SIMULINK, showcasing its capability to effectively track the reference steering angle.

A Multivariate Approach to Quantifying Risk Factors Impacting Stereotactic Robotic-Guided Stereoelectroencephalography.

Stereoelectroencephalography (SEEG) is an important method for invasive monitoring to establish surgical candidacy in approximately half of refractory epilepsy patients. Identifying factors affecting lead placement can mitigate potential surgical risks. This study applies multivariate analyses to identify perioperative factors affecting stereotactic electrode placement. We collected registration and accuracy data for consecutive patients undergoing SEEG implantation between May 2022 and November 2023. Stereotactic robotic guidance, using intraoperative imaging and a novel frame-based fiducial, was used for planning and SEEG implantation. Entry-point (EE), target-point (TE), and angular errors were measured, and statistical univariate and multivariate linear regression analyses were performed. Twenty-seven refractory epilepsy patients (aged 15-57 years) undergoing SEEG were reviewed. Sixteen patients had unilateral implantation (10 left-sided, 6 right-sided); 11 patients underwent bilateral implantation. The mean number of electrodes per patient was 18 (SD = 3) with an average registration mean error of 0.768 mm (SD = 0.108). Overall, 486 electrodes were reviewed. Univariate analysis showed significant correlations of lead error with skull thickness (EE: P = .003; TE: P = .012); entry angle (EE: P < .001; TE: P < .001; angular error: P = .030); lead length (TE: P = .020); and order of electrode implantation (EE: P = .003; TE: P = .001). Three multiple linear regression models were used. All models featured predictors of implantation region (157 temporal, 241 frontal, 79 parietal, 9 occipital); skull thickness (mean = 5.80 mm, SD = 2.97 mm); order (range: 1-23); and entry angle in degrees (mean = 75.47, SD = 11.66). EE and TE error models additionally incorporated lead length (mean = 44.08 mm, SD = 13.90 mm) as a predictor. Implantation region and entry angle were significant predictors of error (P ≤ .05). Our study identified 2 primary predictors of SEEG lead error, region of implantation and entry angle, with nonsignificant contributions from lead length or order of electrode placement. Future considerations for SEEG may consider varying regional approaches and angles for more optimal accuracy in lead placement.

Online path tracking with an integrated H∞ robust adaptive controller for a double-Ackermann steering robot for orchard waypoint navigation

Online path tracking with an integrated H∞ robust adaptive controller for a double-Ackermann steering robot for orchard waypoint navigation

External Steering of Vine Robots via Magnetic Actuation.

This article explores the concept of external magnetic control for vine robots to enable their high curvature steering and navigation for use in endoluminal applications. Vine robots, inspired by natural growth and locomotion strategies, present unique shape adaptation capabilities that allow passive deformation around obstacles. However, without additional steering mechanisms, they lack the ability to actively select the desired direction of growth. The principles of magnetically steered growing robots are discussed, and experimental results showcase the effectiveness of the proposed magnetic actuation approach. We present a 25-mm-diameter vine robot with an integrated magnetic tip capsule, including 6 degrees of freedom (DOF) localization system and camera, and demonstrate a minimum bending radius of 3.85 cm with an internal pressure of 30 kPa. Furthermore, we evaluate the robot's ability to form tight curvature through complex navigation tasks, with magnetic actuation allowing for extended free-space navigation without buckling. The suspension of the magnetic tip was also validated using the 6 DOF localization system to ensure that the shear-free nature of vine robots was preserved. Additionally, by exploiting the magnetic wrench at the tip, we showcase preliminary results of vine retraction. The findings contribute to the development of controllable vine robots for endoluminal applications, providing high tip force and shear-free navigation.

Frameless Stereotactic Biopsy of Brainstem Tumors Using the Stealth Autoguide: A Technical Note.

In the molecular era of neuro-oncology, it is increasingly necessary to obtain tissue for next-generation sequencing and methylome profile for prognosis and targeted oncological management. Brainstem tumors can be technically challenging to biopsy in the pediatric population. Frame-based and frameless techniques have previously been described and proven to be safe and efficacious in children. Recent cranial robotic guidance platforms have augmented the fluency of frameless stereotactic approaches, but the technical nuances of these procedures in children are not often discussed. We present a technical workflow for frameless stereotactic biopsy of brainstem tumors in children using the Medtronic Stealth Autoguide cranial robotic guidance platform and examine safety and efficacy of this surgical approach. A minimally invasive, frameless, transcerebellar approach is described, including operative steps and workflow. We assessed operative times, diagnostic accuracy and yield, and complication rates. Five patients underwent biopsy with the technique described. The youngest patient in our series was of 2 years. The intended target was achieved on postoperative imaging in all cases, and diagnostic tissue was obtained in all 5 patients. One patient had a clinically insignificant hemorrhage. Frameless stereotactic biopsy of the brainstem can be performed safely, efficiently, and accurately using the Medtronic Stealth Autoguide robotic platform in children as young as 2 years.

Robot-Assisted 2D Fluoroscopic Needle Placement-A Phantom Study.

To evaluate the targeting accuracy of a novel robot-assisted guidance technique relying on one pair of 2D C-arm images. In total, 160 punctures were carried out semi-automatically by using a novel robotic device. The needle's paths were planned based on one pair of 2D fluoroscopic images from different angles. Conically shaped aluminum tips inside a gelatin-filled plexiglass phantom served as targets. The accuracy of the needle placement was assessed by taking control CTs and measuring the Euclidean distance (ED) and normal distance (ND) between the needle and the target point. In addition, the procedural time per needle placement was evaluated. The accomplished mean NDs at the target for the 45°, 60°, 75° and 90° angles were 1.86 mm (SD ± 0.19), 2.68 mm (SD ± 0.18), 2.19 mm (SD ± 0.18) and 1.86 mm (SD ± 0.18), respectively. The corresponding mean EDs were 2.32 mm (SD ± 0.16), 2.68 mm (SD ± 0.18), 2.65 mm (SD ± 0.16) and 2.44 mm (SD ± 0.15). The mean duration of the total procedure, including image acquisition, trajectory planning and placement of four needles sequentially, was 12.7 min. Robotic guidance based on two 2D fluoroscopy images allows for the precise placement of needle-like instruments at the first attempt without the need for using an invasive dynamic reference frame. This novel approach seems to be a valuable tool for the precise targeting of various anatomical structures that can be identified in fluoroscopic images.

Comparison of rostral facet joint violations in robotic- and navigation-assisted pedicle screw placement for adult lumbar spine instrumentation

BACKGROUND CONTEXTFacet joint violation by pedicle screws may lead to adjacent-segment disease and postoperative pain. Previous studies have reported the incidence of rostral facet joint violation using various pedicle screw insertion techniques. However, the incidence of facet joint violations with robotic guidance has not been determined. PURPOSETo investigate and compare the incidence of rostral facet joint violation by pedicle screws under robotic guidance and computerized tomography (CT) navigation guidance. STUDY DESIGN/SETTINGRetrospective matched cohort. PATIENT SAMPLEAll patients who underwent robotic-assisted lumbar fusion at a major spine center up until 2023 were retrospectively identified and matched 1:3 to patients undergoing CT navigation guidance based by on age, sex, rostral vertebral level, and length of construct. Inclusion criteria consisted of age greater than 18 years, bilateral pedicle screw fixation, and presence of a postoperative CT scan of the lumbar spine or abdomen/pelvis at any point in the post-operative period. OUTCOME MEASURESRostral facet joint violations. METHODSDescriptive statistics were used to compare cohorts: frequencies, chi-squared analysis for categorical variables, and t-test for continuous variables. RESULTSA total of 408 rostral pedicle screws were implanted in 204 patients (Robot: 102; Navigation: 306). Overall, 13 (12.3%) rostral facet joint violations were observed in the robot cohort and 75 (24.5%) in the navigation cohort (p=.01). Specifically, fewer robotic violations were observed at the L2 (3.5% vs. 32.1%, p=.003) and L3 levels (3.9% vs. 18.1%, p=.08) compared to navigation. No difference was observed at L4 and L5. Bilateral violations are significantly reduced with robotic approaches (5.3% vs. 14.4%, p=.03). Lastly, more facet joint violations were observed during open approaches (robot: 18.8%, navigation: 27.3%) than percutaneous approaches (robot: 11.6%, navigation: 7.1%) in both groups (p<.001). The rate of L4 facet violations was 18.8% in the robotic cohort and 27.3% in the navigation cohort. The rate of L5 facet violations was 31.3% in the robotic cohort and 29.2% in the navigation cohort. CONCLUSIONSUse of robotic assistance in lumbar pedicle screws significantly reduced the rate of rostral facet joint violations compared to navigation guidance at L2 and L3 levels, but not at L4 and L5, with facet violations approaching nearly one-third of the patients at L5 screws. Rostral facet violations can play a significant role in adjacent segment degeneration and disease. Technical factors and trajectory issues likely play a role and addressing these components should minimize unintended facet violation and proximal adding on.

ExoNav: A Novel Robotic Steering and Latching Mechanism for Spinal Cord Stimulation Electrodes

ExoNav: A Novel Robotic Steering and Latching Mechanism for Spinal Cord Stimulation Electrodes

Enhance Kinesthetic Experience in Perceptual Learning for Welding Motor Skill Acquisition with Virtual Reality and Robot-based Haptic Guidance.

Welding is an important operation in many industries, including construction and manufacturing, which requires extensive training and practices. Although welding simulators have been used to accommodate welding training, it is still challenging to enable novice trainees to effectively understand the kinesthetic experience of the expert in an egocentric manner, such as the proper way of force exertion in complex welding operations. This study implements a robot-assisted perceptual learning system to transfer the expert welders' experience to trainees, including both the positional and force control actions. A human-subject experiment (N = 30) was performed to understand the motor skill acquisition process. Three conditions (control, robotic positional guidance with force visualization, and force perceptual learning with position visualization) were tested to evaluate the role of robotic guidance in welding motion control and force exertion. The results indicated various benefits related to task completion time and force control accuracy under the robotic guidance. The findings can inspire the design of future welding training systems enabled by external robotic systems.

Lateral Corpectomy for Tumor at L1: A Surgical Technique: 2-Dimensional Operative Video.

The thoracolumbar junction is a complex and challenging anatomical region due to its heterogeneous array of planes and structures.1 Navigating this region during a lateral approach to the spine is a challenge that requires a thorough understanding of the anatomy. We present a case of a 54-year-old woman with a 7-year history of breast cancer who presented with low back pain after running a marathon. To date, the patient had deferred medical management. Imaging revealed Stage IV differentiated invasive ductal carcinoma with extensive bony metastatic disease in multiple areas of the spine. The patient underwent a right-sided minimally invasive retrodiaphragmatic approach to the thoracolumbar junction for L1 corpectomy, placement of an expandable cage, and posterior percutaneous pedicle screw segmental fixation from T11 to L3 with robotic guidance. Patient consent was obtained for the following procedure, and IRB approval was not required for publication of this single patient case report.

The Future of Artificial Intelligence in Surgery.

Until recently, innovations in surgery were largely represented by extensions or augmentations of the surgeon's perception. This includes advancements such as the operating microscope, tumor fluorescence, intraoperative ultrasound, and minimally invasive surgical instrumentation. However, introducing artificial intelligence (AI) into the surgical disciplines represents a transformational event. Not only does AI contribute substantively to enhancing a surgeon's perception with such methodologies as three-dimensional anatomic overlays with augmented reality, AI-improved visualization for tumor resection, and AI-formatted endoscopic and robotic surgery guidance. What truly makes AI so different is that it also provides ways to augment the surgeon's cognition. By analyzing enormous databases, AI can offer new insights that can transform the operative environment in several ways. It can enable preoperative risk assessment and allow a better selection of candidates for procedures such as organ transplantation. AI can also increase the efficiency and throughput of operating rooms and staff and coordinate the utilization of critical resources such as intensive care unit beds and ventilators. Furthermore, AI is revolutionizing intraoperative guidance, improving the detection of cancers, permitting endovascular navigation, and ensuring the reduction in collateral damage to adjacent tissues during surgery (e.g., identification of parathyroid glands during thyroidectomy). AI is also transforming how we evaluate and assess surgical proficiency and trainees in postgraduate programs. It offers the potential for multiple, serial evaluations, using various scoring systems while remaining free from the biases that can plague human supervisors. The future of AI-driven surgery holds promising trends, including the globalization of surgical education, the miniaturization of instrumentation, and the increasing success of autonomous surgical robots. These advancements raise the prospect of deploying fully autonomous surgical robots in the near future into challenging environments such as the battlefield, disaster areas, and even extraplanetary exploration. In light of these transformative developments, it is clear that the future of surgery will belong to those who can most readily embrace and harness the power of AI.

Initial United States experience with Medtronic Stealth Autoguide cranial robotic guidance platform.

Stereotactic techniques play an important role in neurosurgery. The development of a miniaturized cranial robot with an efficient workflow and accurate surgical execution is an important step in a broader application of these techniques. Herein, the authors describe their experience with the Medtronic Stealth Autoguide miniaturized cranial robot. A retrospective review of 75 cases from 2020 to 2022 was performed. The patients who had undergone surgery utilizing the Stealth Autoguide robot were analyzed for surgical indication and accuracy, operative time, and clinical outcome. The outcomes were defined as follows: for stereoelectroencephalography (SEEG), the electrode placement pattern that identified the seizure focus and did not require any revision or additional leads; for biopsy, the percentage of cases in which diagnostic tissue was obtained; and for laser interstitial thermal therapy (LITT), the percentage of cases in which laser fiber placement was adequate for ablation. Surgical complications were defined as any asymptomatic or symptomatic intracerebral hemorrhage, new neurological deficit, or need for electrode, laser fiber, or biopsy needle repositioning or revision. The Stealth Autoguide robot was utilized in 75 on-label cases, including 40 SEEG cases for seizure focus localization, 19 LITT cases, and 16 stereotactic biopsy cases. The mean real target error (RTE) at the entry was 1.48 ± 0.84 mm for biopsy, 1.36 ± 0.89 mm for Visualase laser fiber placement, and 1.24 ± 0.72 mm for SEEG. The mean RTE at the target was 1.56 ± 0.95 mm for biopsy needle placement, 1.42 ± 0.93 mm for Visualase laser fiber placement, and 1.31 ± 0.87 mm for SEEG electrode placement. The surgical time for unilateral SEEG cases took an average 52 minutes (average 6.5 mins/lead, average 8 electrodes). Bilateral SEEG cases took an average 105 minutes (average 7.5 mins/lead, average 14 electrodes). In the SEEG population, there were no revised or unsuccessful seizure localizations. For biopsy, diagnostic tissue was obtained in 100% of cases. For LITT, fiber placement was adequate for ablation in 100% of cases. There were no cases of symptomatic or asymptomatic intracerebral hemorrhage, and no cases required repositioning or replacement of the laser fiber, electrode, or biopsy needle. One patient experienced transient cranial nerve III palsy following laser ablation that resolved in 10 weeks. A failure of communication between the robotic platform and the Stealth Autoguide as a station required the cancellation of 1 procedure. The Medtronic Stealth Autoguide robot system is versatile across biopsy, SEEG, and laser ablation indications. Setup and surgical execution are efficient with a high degree of accuracy and consistency.

Artificial Intelligence in Spinal Imaging and Patient Care: A Review of Recent Advances.

Artificial intelligence (AI) is transforming spinal imaging and patient care through automated analysis and enhanced decision-making. This review presents a clinical task-based evaluation, highlighting the specific impact of AI techniques on different aspects of spinal imaging and patient care. We first discuss how AI can potentially improve image quality through techniques like denoising or artifact reduction. We then explore how AI enables efficient quantification of anatomical measurements, spinal curvature parameters, vertebral segmentation, and disc grading. This facilitates objective, accurate interpretation and diagnosis. AI models now reliably detect key spinal pathologies, achieving expert-level performance in tasks like identifying fractures, stenosis, infections, and tumors. Beyond diagnosis, AI also assists surgical planning via synthetic computed tomography generation, augmented reality systems, and robotic guidance. Furthermore, AI image analysis combined with clinical data enables personalized predictions to guide treatment decisions, such as forecasting spine surgery outcomes. However, challenges still need to be addressed in implementing AI clinically, including model interpretability, generalizability, and data limitations. Multicenter collaboration using large, diverse datasets is critical to advance the field further. While adoption barriers persist, AI presents a transformative opportunity to revolutionize spinal imaging workflows, empowering clinicians to translate data into actionable insights for improved patient care.

Spatial guidance and control of a space robot during flights in a low-orbit constellation of earth observation mini-satellites

Spatial guidance and control of a space robot during flights in a low-orbit constellation of earth observation mini-satellites

Attitude and position control for formation flying of space robots equipped with a robotic manipulator

This paper presents a novel six degree-of-freedom guidance and control algorithm for free-flyer robots equipped with a robotic manipulator operating on the International Space Station. The proposed algorithm combines a sliding mode controller for rotational motion and a model predictive controller for translational motion. A novel prediction-twisting sliding mode controller (PT-SMC) is introduced to stabilize configuration changes induced by the manipulator and correlated disturbances and to achieve a trade-off among control law flexibility, robustness, and accuracy. The proposed PT-SMC is shown to have improved stability compared to a first-order sliding mode controller. Model predictive control is investigated as a position controller to achieve formation flight between multiple free flyers in a constrained environment, and a leader–follower approach is used to move a triangular formation of robots. A control allocation problem is solved to address the subdivision of attitude and position controls between twelve thrusters. Simulation results of multiple robots approaching a target object demonstrate the improved performance of the proposed control approaches.

Level-specific comparison of 3D navigated and robotic arm-guided screw placement: an accuracy assessment of 1210 pedicle screws in lumbar surgery

BACKGROUND CONTEXTRobotic spine surgery, utilizing 3D imaging and robotic arms, has been shown to improve the accuracy of pedicle screw placement compared to conventional methods, although its superiority remains under debate. There are few studies evaluating the accuracy of 3D navigated versus robotic-guided screw placement across lumbar levels, addressing anatomical challenges to refine surgical strategies and patient safety. PURPOSEThis study aims to investigate the pedicle screw placement accuracy between 3D navigation and robotic arm-guided systems across distinct lumbar levels. STUDY DESIGNA retrospective review of a prospectively collected registry. PATIENT SAMPLEPatients undergoing fusion surgery with pedicle screw placement in the prone position, using either via 3D image navigation only or robotic arm guidance. OUTCOME MEASURERadiographical screw accuracy was assessed by the postoperative computed tomography (CT) according to the Gertzbein-Robbins classification, particularly focused on accuracy at different lumbar levels. METHODSAccuracy of screw placement in the 3D navigation (Nav group) and robotic arm guidance (Robo group) was compared using Chi-squared test/Fisher's exact test with effect size measured by Cramer's V, both overall and at each specific lumbosacral spinal level. RESULTSA total of 321 patients were included (Nav, 157; Robo, 189) and evaluated 1210 screws (Nav, 651; Robo 559). The Robo group demonstrated significantly higher overall accuracy (98.6 vs 93.9%; p<.001, V=0.25). This difference of no breach screw rate was signified the most at the L3 level (No breach screw: Robo 91.3 vs 57.8%, p<.001, V=0.35) followed by L4 (89.6 vs 64.7%, p<.001, V=0.28), and L5 (92.0 vs 74.5%, p<.001, V=0.22). However, screw accuracy at S1 was not significant between the groups (81.1 vs 72.0%, V=0.10). CONCLUSIONThis study highlights the enhanced accuracy of robotic arm-guided systems compared to 3D navigation for pedicle screw placement in lumbar fusion surgeries, especially at the L3, L4, and L5 levels. However, at the S1 level, both systems exhibit similar effectiveness, underscoring the importance of understanding each system's specific advantages for optimization of surgical complications.

Research and Implementation of Robotic Arm Positioning and Grasping Based on Visual Guidance

Abstract This paper proposes a robotic arm vision guidance system based on the ROS platform, which combines the Hikrobot Robotics 2D vision sensor with the Xinsong GCR5 robotic arm to successfully realise vision-guided robotic arm positioning and grasping. Camera calibration, hand-eye calibration, and deep learning techniques are used to establish an accurate transformation relationship between the base coordinate system of the robotic arm and the camera coordinate system to achieve efficient target goal recognition and localisation. Adopting the MoveIt framework and RRT-connect algorithm, the robotic arm can flexibly plan the movement path and successfully complete the target grasping, which provides the theoretical basis and practical experience for robotic arm intelligent grasping.

Assessment of average femoral component rotation for balancing functionally aligned total knee replacement in varus deformity: Robotic image guidance study

Introduction and purposeEnsuring proper femoral component alignment post-Total Knee Arthroplasty (TKA) is crucial for normal patellofemoral (PF) kinematics. However, the customary 3° external rotation relative to the Posterior Condylar Axis (PC Axis) may not universally apply, and the expected final femoral component rotation remains unclear in functionally aligned knees. This study examines the relation between the Transepicondylar Axis (TEA) and PC axis, known as Posterior Condylar Angle (PCA) in Indian patients along with factors influencing PCA, and the feasibility of reproducing patient-specific PCA using image-guided Cuvis joint robot. MethodsForty patients (52 Knees) with primary osteoarthritis and varus deformity were prospectively evaluated. Native PCA was determined using CT-based J planner. Pre-operative patellar shape, PF tilt, PF shift, final femoral component rotation (representing post-operative PCA), final patellar tracking, and post-operative functional and radiological assessment at 3 months were recorded. ResultsStudy participants averaged 64.3 years of age, with a female-to-male ratio of 23 to 17. Varus deformities varied, with IA2 being most prevalent, and sagittal plane deformities included fixed flexion (34.6 %) and hyperextension (44.2 %). The average PCA was 1.9° (range: 0°–7.3°), with most knees (41 out of 52) below 3°. The majority had Wiberg type 1 patellae, with pre-operative patellar tilt averaging 5.63°, reducing post-operatively to 4.43°. Most patients (37 out of 40) achieved excellent Knee Society functional scores at the 3-month mark. Complications included one case of delayed wound healing and one femoral array pin breakage. Notably, our study revealed a significant deviation in PCA from the commonly reported 3° in Western literature, underscoring the need for region-specific considerations in TKA planning. ConclusionPCA of our population is statistically different from customary 3° followed with jig system. Image guided Robotics helps to identify patients specific PCA and reproducing the same was more commonly possible in patients with reducible Varus deformity.

Robotic-assisted total knee arthroplasty is associated with the use of thinner polyethylene liners compared to navigation-guided and manual techniques.

The purpose of this study was to examine the effects of intraoperative technology use on the rate of using polyethylene liners 15 mm or greater during primary total knee arthroplasty (TKA). There were 103,295 implants from 16,386 primary unilateral TKAs performed on 14,253 patients at a single institution between 1 January2018, and 30 June2022, included in the current study. Robotic assistance and navigation guidance were used in 1274 (8%) and 8345 (51%) procedures, respectively. The remaining 6767 TKAs (41%) were performed manually. Polyethylene liners were manually identified and further subcategorised by implant thickness. Patients who underwent robotic-assisted TKA were younger (p < 0.001) and more likely to be male (p < 0.001) compared to patients who underwent navigation-guided or manual TKAs. Average polyethylene liner thickness was similar between groups (10.5 ± 1.5 mm for robotic-assisted TKAs, 10.9 ± 1.8 mm for navigation-guided TKAsand 10.8 ± 1.8 mm for manual TKAs). The proportions of polyethylene liners 15 mm or greater used were 4.9%, 3.8%and 1.9% for navigation-guided, manual and robotic-assisted procedures, respectively (p < 0.001). Multivariate regression analyses demonstrated that navigation-guided (odds ratio [OR]: 2.6, 95% confidence Interval [CI]: [1.75-4.07], p < 0.001) and manual (OR: 2.0, 95% CI: [1.34-3.20], p = 0.001) procedures were associated with an increased use of polyethylene liners 15 mm or greater. Robotic-assisted TKA was associated with a lower proportion of polyethylene liners 15 mm or greater used compared to navigation-guided and manual TKA. These findings suggest that robotic assistance can reduce human error via a more precise cutting system, limit over-resection of the tibia and flexion-extension gap mismatchand ultimately allow for more appropriately sized implants. Level III, retrospective cohort study.