Robotic-Assisted Surgery: State-of-the-Art Development, Clinical

Challenges, and Future Directions

Ruiwen Zhu

College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, 400030, China

Keywords: Surgical Robotics, Minimally Invasive Surgery, Precision Medicine.

Abstract: Surgical robots, as an advanced integration of artificial intelligence, precision engineering, and biomedical

technology, have gained widespread adoption in modern clinical practice. This paper provides a

comprehensive review of the current advancements, challenges, and future trends in surgical robotics across

multiple specialties, including laparoscopic, orthopedic, neurosurgical, cardiovascular interventional, and

puncture robots. While robotic systems have demonstrated superior precision, minimal invasiveness, and

improved clinical outcomes compared to traditional methods, significant challenges remain, such as high costs,

limited haptic feedback, and technical complexities in certain procedures. For instance, the Da Vinci system

has revolutionized minimally invasive surgery but faces economic sustainability issues. Future directions

emphasize AI-enhanced preoperative planning, multi-modal imaging fusion, miniaturization, and 5G-enabled

remote surgery, which promise to further refine robotic precision, expand accessibility, and optimize surgical

workflows. By analyzing these developments, this paper aims to offer valuable insights for researchers and

industry stakeholders, facilitating the evolution of surgical robotics toward greater intelligence, affordability,

and clinical efficacy.

1 INTRODUCTION

With the continuous advancement of clinical

medicine, surgical robots have become increasingly

mature in multidisciplinary clinical applications.

They are now widely utilized in procedures such as

hysterectomy, prostatectomy, lobectomy, and spinal

pedicle screw implantation, demonstrating clinical

outcomes comparable to or even superior to

traditional surgery, particularly in complex

operations where they exhibit higher precision and

safety (Neis et al., 2024, Ping et al., 2024, Xue et al.,

2024). Undoubtedly, as a product of the deep

integration of artificial intelligence, precision

engineering, and biomedical technology, surgical

robots are driving modern surgical practices into a

new era of intelligence and precision. Recent

breakthroughs in 5G remote control, augmented

reality (AR) navigation, and autonomous decision-

making algorithms have further expanded their

application scope, covering specialized fields such as

general surgery, orthopedics, neurosurgery, and even

vascular interventions. However, these surgical

robots also faces numerous challenges, including high

costs leading to poor economic accessibility, low

cost-effectiveness, and unsustainable economic

models. Investigating the current status and trends in

this field, as well as analyzing key bottlenecks in

clinical translation, will contribute to enhancing the

efficacy of surgical robots and better serving public

healthcare.

This paper aims to provide a comprehensive

analysis and overview of the current developments,

challenges, and future trends in laparoscopic surgical

robots, orthopedic surgical robots, neurosurgical

robots, cardiovascular interventional robots, and

puncture robots, with the goal of offering

multidimensional insights for scientific research and

industrial advancement in the field of medical

robotics.

2 LAPAROSCOPIC SURGICAL

ROBOTS

Laparoscopic surgical robots represent an advanced

medical device that integrates traditional laparoscopic

Zhu, R.

Robotic-Assisted Surgery: State-of-the-Art Development, Clinical Challenges, and Future Directions.

DOI: 10.5220/0014362900004718

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence (EMITI 2025), pages 565-573

ISBN: 978-989-758-792-4

565

techniques with robotic technology, aiming to

enhance surgical precision, flexibility, and safety.

The fundamental principle involves performing

minimally invasive surgery through remotely

operated robotic arms, reducing surgeon hand fatigue

and surgical trauma while providing clearer three-

dimensional visualization and more stable instrument

control. Typically, a laparoscopic surgical robot

system consists of a master console, slave devices,

and surgical instruments. The master console allows

surgeons to remotely control the robotic arms via

joysticks or foot pedals, while the slave devices

include multi-degree-of-freedom robotic arms and an

endoscope for precise instrument manipulation and

real-time imaging.

2.1 Thoracic Laparoscopic Robot

In thoracic surgery, robot-assisted thoracoscopic

surgery (RATS) is increasingly becoming

mainstream in lung cancer treatment. The PORTaL

study (n=6,646 cases) demonstrated that robotic

lobectomy outperformed conventional thoracoscopic

surgery in terms of intraoperative blood loss, number

of lymph nodes dissected, and postoperative

complication rates, highlighting its feasibility and

safety (Lee et al., 2024). Single-port robotic

lobectomy (SP-RATS) has shown low postoperative

complication rates (e.g., median hospital stay of 3

days and a conversion-to-thoracotomy rate of only

0.8%) in treating large tumors (such as NSCLC with

diameters >5 cm), making it a viable alternative in

select cases and for experienced surgeons (Lee et al.,

2024). The RAVAL trial further confirmed that the

robot-assisted group exhibited lower postoperative

pain scores and shorter hospital stays (average

reduction of 1.5 days) in early-stage lung cancer

treatment (Lee et al., 2024).

In mediastinal tumor resection, particularly for

complex anterior and posterior mediastinal lesions,

robotic systems demonstrate significant advantages.

Single-port robotic technology reduces postoperative

trauma through high-precision maneuvers, leading to

shorter recovery times and decreased analgesic

requirements. This approach enables bilateral

visualization, particularly in identifying the left

phrenic nerve, while the flexibility of robotic wristed

instruments and adjustable cameras enhances surgical

safety and efficiency (Manolache et al., 2023). The

robotic 3D visualization and articulating instruments

facilitate systematic lymph node dissection (e.g.,

mediastinal lymph nodes), significantly increasing

the average number of lymph nodes retrieved (≥10

stations) and reducing the risk of missed lesions

(Cerfolio et al., 2017).

Regarding improvements in robotic arm precision

and flexibility, the da Vinci Xi system exemplifies

advancements. Compared to the Si system, all Xi

instruments feature extended arm lengths, while the

inter-arm distance can be reduced from 6 cm (Si) to 8

cm (Xi). An additional joint (patient clearance joint)

allows the arms to rotate away from the patient’s body

or other arms, minimizing collisions and enhancing

maneuverability. Furthermore, as shown in Fig. 1, the

Xi platform incorporates a laser alignment system and

an integrated stapler, further improving surgical

accuracy and safety (Ricciardi et al., 2017).

Figure 1: Xi surgical cart positioning: laser crossair

(Ricciardi et al., 2017).

2.2 Gynecological Laparoscopic Robot

Compared to traditional gynecological surgery,

robot-assisted surgery demonstrates superior

precision and safety in gynecologic oncology. The

latest Xi Da Vinci surgical system incorporates a

four-arm architecture, Firefly™ fluorescence

imaging (for real-time tissue perfusion assessment),

and an optimized port placement strategy,

significantly improving accessibility in deep pelvic

dissection (Matsuura et al., 2024). Its enhanced

targeting system minimizes arm collision risks,

facilitating complex procedures such as

lymphadenectomy in ovarian cancer with greater

efficiency (Settnes & Topsoee, 2015).

In benign gynecological surgeries, including

ovarian cystectomy, the Senhance® robotic system

has gained widespread adoption. By integrating

haptic feedback and eye-tracking technology, it

achieves comparable efficacy to conventional

laparoscopy while reducing surgeon fatigue. Unlike

the Da Vinci® system, Senhance® employs reusable

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566

instruments, allowing surgeons to leverage their

laparoscopic expertise more effectively and

addressing some limitations of the Da Vinci®

platform (Šiaulys, 2019).

China’s domestically developed "MicroHand S"

robotic system has also seen preliminary applications

in gynecology. Featuring 7-degree-of-freedom

instruments and 3D visualization, it has been

successfully used in single-port laparoscopic ovarian

cystectomy, with costs over 30% lower than imported

systems (Šiaulys, 2019).

Additionally, Medtronic’s HUGO™ RAS system,

a newly launched robotic-assisted surgery platform,

has demonstrated its capability in cadaveric

gynecological studies. The system efficiently

performed various surgical tasks—including

retraction, cutting, coagulation, and dissection—

across different anatomical regions without technical

complications. Its customizable docking

configuration allows adaptation to complex pelvic

surgeries, such as radical ovarian cancer resection

(Alletti et al., 2022).

3 UROLOGICAL

LAPAROSCOPIC ROBOT

Robot-assisted surgery has been widely adopted in

various urological procedures, including

pyeloureterectomy, adrenal tumor resection, lymph

node dissection, and radical laparoscopic

lymphadenectomy for nonseminomatous testicular

cancer. These robotic techniques enhance surgical

precision and safety while minimizing trauma and

shortening recovery time (Autorino & Porpiglia,

2020).

Recent advancements in intraoperative imaging

have achieved significant breakthroughs.

Indocyanine green (ICG) labeling of vascular and

lymphatic systems substantially improves

intraoperative visualization of anatomical structures.

In robot-assisted partial nephrectomy (RPN), near-

infrared fluorescence (NIRF) imaging enables precise

identification of renal artery branches, reducing

intraoperative bleeding risks. The combination of

ICG and NIRF enhances landmark recognition,

facilitates complex reconstruction, and improves

oncological outcomes (Cacciamani et al., 2020).

Further integration of intraoperative ultrasound

and 3D modeling enables real-time surgical

navigation. For instance, the NeuroSAFE technique

(nerve-sparing frozen section analysis during robotic

prostatectomy) combines frozen-section pathology

and augmented reality (AR) guidance to optimize

nerve-sparing surgery (NSS) in radical prostatectomy

(RP). Studies demonstrate that NeuroSAFE increases

the number of patients eligible for NSS without

compromising surgical margin status or biochemical

recurrence (BCR) rates (van der Slot et al., 2022).

Artificial intelligence (AI) integration in robotic

surgery demonstrates significant advancements

across the surgical workflow. For preoperative

planning, deep learning techniques enable automated

analysis of CT and MRI images to identify and

segment critical anatomical structures including

tumors, blood vessels, and organs. During

intraoperative navigation, the combination of robotic

systems with deep learning algorithms facilitates real-

time tracking of surgical instruments and internal

organs, ensuring surgical precision. Machine learning

models further analyze intraoperative data to provide

real-time decision support regarding optimal

resection paths and avoidance of critical structures.

Postoperatively, deep learning technology automates

image analysis to evaluate surgical outcomes,

assessing tumor resection completeness and residual

lesions (Bellos et al., 2024).

4 ORTHOPEDIC SURGICAL

ROBOTS

Orthopedic surgical robots represent a technological

platform that integrates robotic arms, navigation

systems, and artificial intelligence assistance to

achieve precise bone positioning, implant placement,

and minimally invasive procedures. The core value

lies in surpassing the limitations of manual operations

while enhancing surgical standardization and

reproducibility. Through advancements in navigation

accuracy, AI integration, and robotic arm flexibility,

these systems have significantly improved clinical

outcomes in hip/knee arthroplasty and spinal

surgeries.

The Stryker Mako system utilizes CT scans to

generate patient-specific 3D bone models, combined

with haptic feedback-enabled robotic arms, reducing

acetabular cup positioning errors to within 1°. By

integrating 3D preoperative planning with

intraoperative robotic assistance, surgeons benefit

from real-time feedback to ensure accurate acetabular

cup placement and leg length restoration. The system

Robotic-Assisted Surgery: State-of-the-Art Development, Clinical Challenges, and Future Directions

567

merges preoperative planning with robotic execution,

allowing surgeons to prepare the acetabulum and

precisely position the cup using a handheld robotic

arm, minimizing complications (Ram et al., 2023).

A flexible drilling system developed by the

University of Hamburg enables curved femoral

milling in total hip arthroplasty (THA). The

experimental team tested the integrated system—

comprising mechanical assembly, embedded position

sensing, optical tracking, and navigation—on

sawbone models. Results demonstrated milling

boundary accuracy of 75.232% within ±1SD and

93.924% within ±2SD, confirming its capability to

perform curved-path milling in femurs, addressing

challenges posed by complex anatomy inaccessible to

rigid tools (Fujad et al., 2018).

Figure 2: “Tuoshou” Robotic base station (A), optical

tracking system (B), and toolset (C) (Chang, J., et al., 2022).

Nanjing Tuoshou Medical’s high-precision

surgical robot, "Tuoshou," employs deep learning

algorithms to intraoperatively identify bone

landmarks in real time, reducing registration duration.

As shown in Fig.2, The robot consists of a robotic

base station, an optical tracking system (OTS), and a

toolset for navigation and positioning, together with

surgical navigation and positioning software. In a

multicenter randomized controlled trial comparing

thoracolumbar pedicle screw fixation with the

TiRobot system, safety assessments revealed no

significant differences in operative time, instrument

success rate, technical success rate, or procedural

success rate. However, the Tuoshou group exhibited

smaller K-wire placement deviations and higher

pedicle screw accuracy than the TiRobot group,

demonstrating superior precision and reduced

invasiveness for spinal applications (Chang et al.

2022, Gandhi, 2023).

5 NEUROSURGICAL ROBOTS

Neurosurgical robotic systems represent an advanced

integration of robotic arms, image-guided navigation,

and artificial intelligence, designed to enhance

procedural safety through precise positioning and

stabilized operation. Recent breakthroughs in this

field focus on three key areas: frameless high-

precision localization, flexible miniaturized designs,

and multimodal image fusion.

Kim et al. developed an MRI-compatible

continuum robot capable of navigating narrow

anatomical pathways to access deep brain regions

while minimizing collateral tissue damage. Utilizing

smart materials (e.g., McKibben pneumatic artificial

muscles), these robots achieve high-precision

bending and extension, adapting to intricate

intracranial environments (Gandhi, 2023). Advances

in soft robotics have further expanded neurosurgical

applications, with researchers implementing sliding

mode control for stretchable soft robotic modules to

improve motion accuracy and response speed,

thereby enhancing stability in dynamic brain tissue

(Gandhi, 2023).

For multimodal image fusion, the ROSA One

system employs 3D structured light technology to

achieve submillimeter registration accuracy. By

integrating real-time imaging updates to compensate

for brain shift caused by cerebrospinal fluid loss, it

addresses localization inaccuracies inherent in

conventional navigation (Zhou et al., 2023). Modern

deep learning models can predict tumor margins and

vascular distribution, enabling robotic systems to

optimize surgical trajectories. The CyberKnife

system, leveraging AI-driven respiratory

synchronization, maintains 0.5 mm targeting

precision in spinal radiosurgery (Eljamel, 2008).

Additionally, neurosurgical robots are being

integrated with virtual reality (VR) simulation

platforms. As shown in Fig.3, the Lindbergh surgical

rehearsal system allows surgeons to train for complex

procedures in a virtual environment, shortening the

learning curve. A collaborative effort between

Mexico’s National Autonomous University and the

University of Tokyo introduced an interactive VR

simulator for transsphenoidal tumor resection. Its

dynamic motion scaling (DMS) feature refines fine

motor control near target areas, reducing healthy

tissue damage. Although this approach increases

operative time, it significantly improves safety

(Heredia-Pérez et al., 2019).

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(a)

(b)

Figure 3: Interactive VR simulator for transsphenoidal

tumor resection (Heredia-Pérez et al., 2019). (a) User

interacting with the simulator through two haptic interfaces

and a stereo‐monitor; (b) screenshot of the simulation

indicating virtual components

6 CARDIOVASCULAR

INTERVENTIONAL ROBOTS

Cardiovascular surgical robotics is a technology that

utilizes robotic systems to assist surgeons in

performing minimally invasive procedures on the

heart and blood vessels. Its core lies in integrating

three-dimensional high-definition imaging, multi-

degree-of-freedom robotic arms, and remote control

technologies to overcome the physical limitations of

traditional surgery. In recent years, key technological

innovations have been achieved in structural design

and material advancements, AI-assisted instrument

tracking, as well as force feedback and operational

precision.

The third-generation robotic system, co-developed

by Beijing Institute of Technology and Kagawa

University, employs dual linear sliding mechanisms

to enable simultaneous delivery of catheters and

guidewires. Equipped with advanced force-sensing

capabilities, the system supports coordinated

manipulation of catheters and guidewires, surpassing

human surgeons in performance and enabling more

intricate and complex surgical procedures (Zhao et

al., 2022).

A convolutional neural network (CNN)-based

cross-frame real-time recognition model has

demonstrated high accuracy and stability in tracking

and localizing surgical instruments. Specifically, the

model exhibits a low RMSE value, indicating

minimal positioning error, while its high AUC value

confirms superior accuracy in distinguishing different

instrument states, thereby replacing traditional

manual assessment (Zhang et al., 2024).

Meta’s Segment Anything Model (SAM), trained

on over 110 million medical images, achieves zero-

shot transfer learning for segmentation tasks,

adapting to novel image distributions while matching

the performance of fully supervised models. Users

can guide the model via various prompts—such as

clicks, bounding boxes, or text descriptions—to

facilitate target segmentation. The optimized SAM

operates efficiently in real-time environments,

making it suitable for time-sensitive applications

(Zhang et al., 2024).

Researchers from the Medical Robotics and

Micro-Nano Devices Research Center at the

Shenzhen Institute of Advanced Technology, Chinese

Academy of Sciences, have designed and developed

a compact 2-degree-of-freedom (2-DOF) robotic

catheter system. By employing long short-term

memory (LSTM) and gated recurrent unit (GRU)

networks, the system predicts the slave robot’s

position and computes appropriate compensation

values. Simulation studies in CoppeliaSim and

physical experiments validate the effectiveness of the

neural network controller. Results demonstrate that

the controller significantly enhances master-slave

position tracking while minimizing positional errors,

contributing to autonomous navigation and improved

patient safety (Ricciardi et al., 2017).

7 PUNCTURE ROBOTS

Puncture robots are automated medical devices

typically composed of robotic arms, sensors, control

systems, and image-guidance modules. They are

designed to perform precise and navigated puncture

procedures on targeted tissues or organs within the

patient's body. The robotic arm executes the puncture

operation, while integrated sensors provide real-time

monitoring of needle position and orientation to

ensure procedural accuracy. The control system

utilizes image-processing algorithms to determine

Robotic-Assisted Surgery: State-of-the-Art Development, Clinical Challenges, and Future Directions

569

optimal puncture trajectories and guides the robot in

performing highly precise maneuvers. Due to their

ability to enhance surgical precision, reduce

physician radiation exposure, minimize patient

discomfort, and alleviate clinician workload, these

robotic systems are widely adopted in interventional

radiology, oncology, and ultrasonography.

7.1 Interventional Radiology Puncture

Robot

Interventional radiology puncture robots integrate

robotic arms and control systems with advanced

imaging modalities such as CT, MRI, and ultrasound

to perform a variety of clinical functions, including

biopsy, ablation therapy, injection therapy, and

neurointerventions. These robotic systems have been

widely adopted in vascular interventions, particularly

in coronary, peripheral, and neurovascular

procedures. Commercial platforms such as the

CorPath GRX and Magellan Robotic System leverage

remote-control technology to achieve precise

manipulation of guidewires and catheters,

significantly reducing operator fatigue while

enhancing procedural stability. Studies have

demonstrated that these robotic systems achieve

comparable—if not superior—precision compared to

manual techniques (Zhang et al., 2024).

In musculoskeletal interventions, puncture robots

are extensively utilized for needle biopsies, deep

brain stimulation electrode placement, and skull-base

biopsies. For instance, as shown in Fig.4, in bone

biopsy procedures, augmented reality (AR)-guided

navigation systems enable real-time overlay of digital

Figure 4: CT-Guided Lumbar Biopsy with AR Navigation

system (Albano et al., 2023).

content onto the surgical field, substantially reducing

the number of required CT scans and radiation

exposure. This advancement not only minimizes

patient radiation dose but also shortens procedural

duration while maintaining safety and efficacy

(Albano et al., 2023).

7.2 Oncology Puncture Robot

Oncology puncture robots represent an advanced

integration of medical imaging navigation (including

CT, MRI, and ultrasound) with robotic manipulator

systems, designed to assist physicians in performing

percutaneous biopsies, ablations, and other minimally

invasive procedures with high-precision targeting and

trajectory planning. By leveraging CT or MRI-based

image guidance, these robotic systems achieve

accurate tumor localization. Equipped with multi-

degree-of-freedom robotic arms, they enable flexible

needle insertion at various angles while maintaining

operational stability.

During the puncture procedure, the system

provides real-time visualization of needle tip position

and insertion trajectory to ensure targeting accuracy.

Furthermore, the robotic platform can autonomously

optimize puncture paths based on patient-specific

anatomical considerations, thereby avoiding critical

tissues and organs. These technological

advancements not only improve procedural success

rates and reduce complications but also significantly

decrease physicians' radiation exposure, enhancing

overall operational safety (Kissler & Settmacher,

2016).

7.3 Ultrasound-Guided Puncture

Robot

Ultrasound-guided puncture robots represent an

advanced medical technology that integrates real-

time ultrasonic imaging with robotic control systems

to achieve highly accurate percutaneous procedures.

These systems employ three core technological

components: (1) multi-degree-of-freedom robotic

positioning, (2) dynamic ultrasound image feedback,

and (3) intelligent control algorithms.

In prostate cancer diagnostics, Stoianovici et al.

developed an MRI-compatible robotic system for

transrectal ultrasound (TRUS)-guided prostate

biopsies. The system's modular design achieved

submillimeter needle positioning accuracy (<1 mm),

with clinical validation leading to FDA clearance. For

breast interventions, Navarro-Alarcon et al. created a

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compact robotic system featuring ultrasonic motor

actuation and Bowden cable transmission, enabling

MRI-compatible remote operation with 1.29 mm

targeting precision. This system's open-control

architecture significantly enhanced trajectory

planning flexibility for complex breast biopsy

procedures (Palep, 2009).

8 DISCUSSION

Despite remarkable advancements and demonstrated

innovation potential across multiple medical

specialties, the widespread adoption of surgical

robotic systems continues to confront significant

challenges. The most prominent barrier remains the

prohibitively high total cost of ownership. Taking the

da Vinci Surgical System as a representative

example, the initial capital expenditure encompasses

not only the robotic console and associated

peripherals (including specialized instruments and

stereoscopic camera systems) but also installation and

comprehensive training programs, with complete

system configurations frequently exceeding several

million dollars (Longmore et al., 2020). Furthermore,

recurring operational expenses - comprising single-

use disposable instruments, periodic maintenance

contracts, and mandatory recalibration of reusable

robotic arms - substantially increase the lifetime cost

of ownership.

Within the domain of laparoscopic robotic

systems, current technological limitations manifest

primarily as prolonged operative durations

(particularly evident in complex procedures such as

pancreaticoduodenectomies) and the absence of

sophisticated haptic feedback mechanisms (Kissler &

Settmacher, 2016). This tactile deficiency forces

surgeons to rely exclusively on visual compensation

for precision control, potentially elevating the risk of

iatrogenic tissue trauma (Sebastian, 2017). Emerging

solutions focus on the integration of multimodal

imaging fusion technologies, combining indocyanine

green fluorescence imaging (e.g., Firefly technology),

real-time intraoperative ultrasonography, and

preoperative CT/MRI datasets to enhance surgical

navigation capabilities (Li et al., 2024).

Gynecological robotic platforms face distinct

technical obstacles including restricted visual fields

during large myomectomy procedures and

insufficient end-effector articulation degrees-of-

freedom (Park et al., 2023). Next-generation systems

are evolving toward precision personalized medicine

through artificial intelligence-enhanced preoperative

planning algorithms. Recent investigations

demonstrate that AI-generated three-dimensional

navigation models can automatically delineate tumor

margins and vascular architecture with 92% accuracy

in endometrial cancer surgeries, establishing reliable

"no-fly zones" that significantly reduce ureteral

injury rates (Knigin et al., 2024).

Orthopedic robotic assistance is currently

constrained by substantial physical footprints (with

systems like the da Vinci occupying approximately

100 cubic feet of operating room space), creating

logistical challenges including cable management

issues and increased infection control concerns (Qi &

Liang, 2018). While device miniaturization and

enhanced precision represent clear developmental

trajectories, these engineering advancements may

perpetuate elevated system costs. Promising research

directions include the development of advanced

multimodal image registration software integrating

CT, MRI, and real-time ultrasound data to expand

soft tissue interaction capabilities, alongside the

implementation of U-Net convolutional neural

networks for optimized bone metastasis identification

and osteotomy path planning (Yuan et al., 2024).

Neurosurgical robotic applications confront

unique material compatibility challenges, where

MRI/PET hybrid imaging systems exhibit

characteristic noise artifacts and spatial registration

inaccuracies (Zhou et al., 2023). The impending

deployment of 5G network infrastructure promises to

enable real-time teleoperated procedures, allowing

expert surgeons to remotely control robotic systems

in underserved medical facilities while maintaining

sub-millisecond latency thresholds (Zhou et al.,

2023).

Cardiovascular robotic platforms, despite

demonstrating measurable advantages in reduced

postoperative recovery periods and decreased

complication rates, continue to face fundamental

technical limitations when managing extracorporeal

circulation-dependent procedures such as multi-

vessel coronary artery bypass grafting (Badhwar et

al., 2023). Maintaining instrument stability during

beating-heart operations remains particularly

challenging. Anticipated technological solutions

include the development of advanced force feedback

systems, miniaturized instrument designs, and AI-

powered decision support modules to enhance

complex case adaptability (Onan, 2018).

Percutaneous robotic systems continue to face

fundamental challenges in targeting accuracy. While

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current technologies integrating CT-based volumetric

reconstruction and six-degree-of-freedom robotic

positioning have achieved submillimeter precision,

persistent issues including image distortion artifacts,

signal noise interference, and needle tip localization

uncertainty still compromise procedural reliability.

To address these challenges, the field is advancing

through several innovative approaches: optimizing

trajectory planning algorithms via deep learning,

implementing augmented reality-based real-time

navigation systems, establishing robust telesurgery

network infrastructure, and promoting international

regulatory harmonization. The convergence of

artificial intelligence and augmented reality

technologies represents the most promising

developmental pathway for enhancing procedural

accuracy and reliability.

These synergistic technological advancements will

systematically address current limitations while

facilitating broader clinical adoption across surgical

specialties, ultimately advancing the paradigm of

precision medicine. As technological breakthroughs

continue to emerge and cost-reduction strategies

mature, surgical robotic systems are positioned to

become indispensable components of future

healthcare delivery systems, offering patients

unprecedented levels of procedural safety and

therapeutic accuracy.

9 CONCLUSION

Through a comprehensive evaluation of five key

domains—laparoscopic, orthopedic, neurosurgical,

cardiovascular interventional, and puncture

robotics—surgical robotic technology has evolved

from a standalone assistive tool into a sophisticated

multi-disciplinary integration platform. The

enhanced lymph node dissection accuracy of the da

Vinci Xi system in thoracic surgery, the superior

pedicle screw placement precision of the Tuoshou

orthopedic robot, and the deep brain maneuverability

of MRI-compatible neurosurgical robots collectively

validate the substantial advantages of robotic systems

in improving surgical safety and minimally invasive

outcomes. Particularly in complex anatomical

regions, robotic platforms incorporating fluorescence

navigation and AI-based preoperative planning

achieve levels of precision unattainable with

conventional techniques.

Nevertheless, critical challenges persist in both

technological and clinical implementation.

Economically, the prohibitively high acquisition

costs and substantial annual maintenance expenses

limit widespread adoption. Technically, the absence

of haptic feedback introduces a 29% risk of potential

tissue damage in laparoscopic procedures, while the

bulky footprint of orthopedic robotic systems

complicates operating room logistics. Additionally,

the lack of standardized training protocols

necessitates an average of 80–120 procedures for

surgeons to achieve proficiency, further hindering

scalability. To realize the democratization of this

technology, a tripartite support framework must be

established: (1) Policy-level interventions to optimize

reimbursement structures and pricing mechanisms;

(2) Industrial advancements to accelerate domestic

production of core components; (3) Clinical

standardization to develop evidence-based surgical

pathways. Only through such coordinated

"technology-industry-clinical" synergy can the goal

of accessible precision medicine be achieved,

extending robotic-assisted care to grassroots medical

institutions. Looking ahead, sustained technological

iteration and innovative care models are poised to

usher in a new era of intelligent, personalized, and

equitable surgical practice.

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