Robotic System Research Articles

Semi-automatic robotic puncture system based on deformable soft tissue point cloud registration.

Traditional surgical puncture robot systems based on computed tomography (CT) and infrared camera guidance have natural disadvantages for puncture of deformable soft tissues such as the liver. Liver movement and deformation caused by breathing are difficult to accurately assess and compensate by current technical solutions. We propose a semi-automatic robotic puncture system based on real-time ultrasound images to solve this problem. Real-time ultrasound images and their spatial position information can be obtained by robot in this system. By recognizing target tissue in these ultrasound images and using reconstruction algorithm, 3D real-time ultrasound tissue point cloud can be constructed. Point cloud of the target tissue in the CT image can be obtained by using developed software. Through the point cloud registration method based on feature points, two point clouds above are registered. The puncture target will be automatically positioned, then robot quickly carries the puncture guide mechanism to the puncture site and guides the puncture. It takes about just tens of seconds from the start of image acquisition to completion of needle insertion. Patient can be controlled by a ventilator to temporarily stop breathing, and patient's breathing state does not need to be the same as taking CT scan. The average operation time of 24 phantom experiments is 64.5 s, and the average error between the needle tip and the target point after puncture is 0.8mm. Two animal puncture surgeries were performed, and the results indicated that the puncture errors of these two experiments are 1.76mm and 1.81mm, respectively. Robot system can effectively carry out and implement liver tissue puncture surgery, and the success rate of phantom experiments and experiments is 100%. It also shows that the puncture robot system has high puncture accuracy, short operation time, and great clinical value.

Optimization design method for typical grassland perception robot system

Optimization design method for typical grassland perception robot system

A flexible proximity-pressure–temperature tri-mode robotic sensor with stimulus discriminability, high sensitivity and wide perception range

Along with the explosive utilization of intelligent and bionic robotics, the rise of somatosensory system with excellent flexibility and multiple biological sensing characteristic emerges as a substantial crux of this domain. Herein, we propose a flexible high-performance multi-mode sensor for real-time proximity–pressure–temperature perception based on a monolithic sensing unit with fingerprint-like hierarchical architecture. The monolithic sensing unit, primarily constituted by a double-permeable ionic liquids/Multi-walled nanotubes conductive network, demonstrates dual-functionality in detecting pressure and temperature. Making use of the further synergy of rational topographical architecture engineering and feasible decoupling algorithm construction, extraordinary progress in sensing performances for both pressure and temperature are attained with negligible mutual interferences. Additionally, the sensor is capable of switching to touchless mode to detect objects at distance up to 200 mm, validating its remarkable proximity sensing ability. The multifunctional nature of sensor is further substantiated through its integration with a robotic hand, highlighting its practical applicability in advanced robotic systems.

Rehabilitation exoskeleton system with bidirectional virtual reality feedback training strategy

AbstractVirtual reality (VR) technology revitalises rehabilitation training by creating rich, interactive virtual rehabilitation scenes and tasks that deeply engage patients. Robotics with immersive VR environments have the potential to significantly enhance the sense of immersion for patients during training. This paper proposes a rehabilitation robot system. The system integrates a VR environment, the exoskeleton entity, and research on rehabilitation assessment metrics derived from surface electromyographic signal (sEMG). Employing more realistic and engaging virtual stimuli, this method guides patients to actively participate, thereby enhancing the effectiveness of neural connection reconstruction—an essential aspect of rehabilitation. Furthermore, this study introduces a muscle activation model that merges linear and non‐linear states of muscle, avoiding the impact of non‐linear shape factors on model accuracy present in traditional models. A muscle strength assessment model based on optimised generalised regression (WOA‐GRNN) is also proposed, with a root mean square error of 0.017,347 and a mean absolute percentage error of 1.2461%, serving as critical assessment indicators for the effectiveness of rehabilitation. Finally, the system is preliminarily applied in human movement experiments, validating the practicality and potential effectiveness of VR‐centred rehabilitation strategies in medical recovery.

Toward a Generic Framework for Mission Planning and Execution with a Heterogeneous Multi-Robot System.

This paper presents a comprehensive framework for mission planning and execution with a heterogeneous multi-robot system, specifically designed to coordinate unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) in dynamic and unstructured environments. The proposed architecture evaluates the mission requirements, allocates tasks, and optimizes resource usage based on the capabilities of the available robots. It then executes the mission utilizing a decentralized control strategy that enables the robots to adapt to environmental changes and maintain formation stability in both 2D and 3D spaces. The framework's architecture supports loose coupling between its components, enhancing system scalability and maintainability. Key features include a robust task allocation algorithm, and a dynamic formation control mechanism, using a ROS 2 communication protocol that ensures reliable information exchange among robots. The effectiveness of this framework is demonstrated through a case study involving coordinated exploration and data collection tasks, showcasing its ability to manage missions while optimizing robot collaboration. This work advances the field of heterogeneous robotic systems by providing a scalable and adaptable solution for multi-robot coordination in challenging environments.

Cluster formation tracking of networked perturbed robotic systems via hierarchical fixed-time neural adaptive approach

This paper investigates the fixed-time cluster formation tracking (CFT) problem for networked perturbed robotic systems (NPRSs) under directed graph information interaction, considering parametric uncertainties, external perturbations, and actuator input deadzone. To address this complex problem, a novel hierarchical fixed-time neural adaptive control algorithm is proposed based on a hierarchical fixed-time framework and a neural adaptive control strategy. The objective of this study is to achieve accurate CFT of NPRSs within a fixed time. Specifically, we design a distributed observer algorithm to estimate the states of the virtual leader within a fixed time accurately. By using these observers, a neural adaptive fixed-time controller is developed in the local control layer to ensure rapid and reliable system performance. Through the use of the Lyapunov argument, we derive sufficient conditions on the control parameters to guarantee the fixed-time stability of NPRSs. The theoretical results are eventually validated through numerical simulations, demonstrating the effectiveness and robustness of the proposed approach.

Upper limb exoskeleton rehabilitation robot inverse kinematics modeling and solution method based on multi-objective optimization

The inverse kinematics problem of exoskeleton rehabilitation robots is challenging due to the lack of a standard analytical model, resulting in a complex and varied solution process. This complexity is especially pronounced in redundant upper limb exoskeleton robots, where inefficient solutions hinder the robot’s ability to adapt to the kinematic shape of the upper limb. This paper proposes a modeling and solution method based on multi-objective optimization to address the inverse kinematics of upper limb exoskeleton robots. We analyzed and validated this method using a redundant upper limb exoskeleton rehabilitation robot system developed by ourselves. First, we established a multi-objective inverse kinematics solution model by defining the end-position function, joint motion comfort function, system energy consumption function, motion safety, and human-like constraints. Then, the solution was designed based on the Improved Equilibrium Optimization (IEO) algorithm and validated its computational performance in terms of optimization ability, accuracy, and robustness. Finally, we experimentally tested the inverse kinematics solution model with the IEO algorithm on discrete objectives and continuous training trajectories using a redundant upper limb exoskeleton rehabilitation robot system. The results show that by incorporating the joint comfort function, system energy consumption function, and human-like constraints into the inverse kinematics model, we can not only quickly solve the inverse kinematics of redundant upper limb exoskeleton robots but also significantly improve the robot’s motion shape. Furthermore, it has better solution accuracy and stronger robustness than other algorithms when solving this inverse kinematics model based on the IEO algorithm.

Total Mesorectal Excision with New Robotic Platforms: A Scoping Review.

Colorectal surgery is one of the specialties that have significantly benefited from the adoption of robotic technology. Over 20 years since the first robotic rectal resection, the Intuitive Surgical Da Vinci system remains the predominant platform. The introduction of new robotic systems into the market has enabled the first documented total mesorectal excision (TME) using alternative platforms. This scoping review aimed to assess the role and adoption of these emerging robotic systems in performing TME for rectal cancer surgery. Methods: A comprehensive search of the Medline, Embase, and Cochrane databases was conducted up to August 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Results: Thirty-six studies were included in the review. The majority of rectal surgical procedures were performed using eight different robotic platforms. Intraoperative, short-term, and functional outcomes were generally favorable. However, pathological results were frequently incomplete. Several studies identified the lack of advanced robotic instruments as a significant limitation. Conclusions: The quality of the resected specimen is critical in rectal cancer surgery. Although TME performed with new robotic platforms appears to be feasible and safe, the current body of literature is limited, particularly in the assessment of pathological and long-term survival outcomes.

Justification of an innovative system for the complete burial of solid, high-level radioactive waste (HLW) in spent open-pit mines

The object of research is the spent open-pit mines themselves where the proposed system could be applied. The primary reason for this studying is the following circumstance: up to the present time period, in all countries of the world, no methods of HLW disposal in a storage facility has been identified that is absolutely safe for any length of time, taking into account the impact of catastrophic natural emergencies and man-made emergencies. The research was conducted to address the problem of safely managing and storing HLW, leveraging the unique characteristics of spent open-pit mines, such as their large volume and geological stability, to prevent environmental contamination and ensure long-term safety. In the article has been justified a novel approach to the burial of sarcophagus containers with solid HLW in exhausted mining pits and studied the usabilities of the basalt sarcofagous container. Robust materials and advanced robotic systems proposed in the article aims to address the challenges associated with long-term radioactive waste disposal effectively. The robotic systems transfer the basalt container with HLW, ensuring personnel safety by minimizing human presence near radioactive materials. In the article have been established the distribution of temperature into the multi-layered composite structure of the basalt sarcophagous with HLW from 300 °C into the inner space to 50 °C onto on the its outer suffer where the thickness of each layers (from inner to outer radius) was respectively: for lead matrix: from r1=0.1 m to r2=0.2 m; for clay layer: from r2=0.2 m to r3=0.3 m; for basalt block: from r3=0.3 m to r4=0.4 m. The findings on temperature distribution are crucial as they directly affect the performance and longevity of the basalt containment system

Tuning PID controller parameters of the DC motor with PSO algorithm

AbstractDirect current (DC) motors have superior features such as operating at different speeds, being affordable and easily controllable. Therefore, DC motors have many uses, such as machine tools and robotic systems in many factories up to the textile industry. The PID controller is one of the most common methods used to control DC motors. PID is a feedback controller with the terms Proportional, Integral, and Derivative. The proper selection of P, I, and D parameters is critical for achieving the desired control in the PID controller. In this study, the transfer function of a DC motor is first obtained, and the speed of the DC motor is controlled by the PID controller using this transfer function. Then, Particle Swarm Optimization (PSO), an optimization method based on swarm intelligence, is used to adjust the P, I, and D parameters. By using the obtained P, I, and D coefficients, the speed of the DC motor is tried to be controlled, and the effect of the filter coefficient on the system output is examined. The performance of the proposed PSO-PID controller with successful results is given in tables and graphics. Control and optimization studies are carried out with MATLAB Simulink.

Adaptive neuro-fuzzy inference system based active force control with iterative learning for trajectory tracking of a biped robot

ABSTRACT We investigate the integration of the active force control (AFC) scheme and the adaptive neuro-fuzzy inference system (ANFIS) as an intelligent controller algorithm to address trajectory-tracking problems in robotic systems, The AFC-ANFIS model exploits iterative learning (IL) to improve the tracking performance based on its trained model. The ANFIS parameters are tuned using both particle swarm optimisation (PSO) and beetle antennae search (BAS) algorithms. The simulation results of two different robots, i.e. a five-link biped robot and a PUMA 560 robot arm, indicate that the proposed AFC-ANFIS controller performs well for trajectory tracking and disturbances rejection. The AFC-ANFIS performance is evaluated and compared with those from other controllers using the average tracking error (ATE) metric. The comparative results reveal that AFC-ANFIS offers a viable approach with a rapid training process to undertaking trajectory tracking and disturbance rejection tasks.

Clinical study on the effects of cluster needling at scalp points with needle retaining combined with the training of the upper-limb intelligent rehabilitation robot on shoulder function in stroke patients during convalescence

To explore the effects of cluster needling at scalp points with needle retaining combined with the training of the upper-limb intelligent rehabilitation robot on shoulder function in stroke patients during convalescence. Ninety stroke patients during convalescence were collected and randomized into scalp point group, robot training group and combined intervention group, with 30 cases each. In the scalp point group, the cluster needling was delivered at scalp points with the needles retained. In the robot training group, the patients were trained with the upper-limb intelligent rehabilitation robot. In the combined intervention group, the patients received both the cluster needling and the training of the upper-limb intelligent rehabilitation robot. In each group, the treatment was given once daily, 5 treatments a week with 2 days rest, for consecutive 4 weeks. Separately, before and after treatment, the score of Fugl-Meyer assessment upper extremity scale (FMA-UE) and the score of activity of daily living (ADL) were evaluated. Using the in-built assessment system of the upper-limb intelligent rehabilitation robot, the range of motion (ROM) of forward flexion, horizontal abduction and horizontal adduction of the affected shoulder joint were evaluated. With surface electromyogram (sEMG), the sEMG value of the deltoid muscle and the pectoralis major on the affected side were detected. Compared with the values before treatment, ADL score and FMA-UA score increased in patients of the three groups (P<0.05), and ROM of forward flexion, horizontal abduction and horizontal adduction of the affected shoulder joint was larger (P<0.05), the sEMG value of the fasciculi pectoralis major anterior of patients in the combined intervention group was reduced (P<0.05), and the sEMG of anterior deltoid tract was elevated in the three groups (P<0.05). When compared with the scalp point group and the robot group, in the combined intervention group, after treatment, ADL score and FMA-UA score were higher (P<0.05), ROM of forward flexion, horizontal abduction and horizontal adduction of the affected shoulder joint elevated (P<0.05) and sEMG value of the fasciculi pectoralis major anterior reduced (P<0.05), while which of the anterior deltoid tract was elevated (P<0.05). The cluster needling at scalp points with needle retaining, combined with the training of the upper-limb intelligent rehabilitation robot, improves the upper limb motor function and the range of motion of the shoulder joint in stroke patients during convalescence.

Anisotropic piezoresistive response of 3D-printed pressure sensor based on ABS/MWCNT nanocomposite

Nanocomposites based on carbon nanotubes (CNTs) are suitable for sensors, due to matrix ability to incorporate nanotube properties. Thus, we developed a low-cost, nanostructured poly(acrylonitrile-butadiene-styrene) (ABS) polymer piezoresistive sensor produced by additive manufacturing. For this, solution layers of acetone, dimethylformamide and CNTs functionalized with carboxylic acid were pulverized on an ABS substrate using an aerograph. Electrical characterization revealed an anisotropic piezoresistive response of the material, induced by the printing lines direction. Field Emission Gun-Scanning Electron Microscopy showed the nanostructured film spreading after five layers of CNTs as well as the random entanglement of nanotubes on parallel and perpendicular 3D-printed ABS substrates. Raman spectroscopy indicated compression and p-type doping of CNTs in interaction with the polymer, as seen mainly by the blueshift of the G and 2D subbands. The results show that the material is promising for pressure sensors, with potential applications in robotic haptic feedback systems.

Robotic Surgery in Pelvic Organ Prolapse: A Retrospective Comparison of Ileopectopexy and Sacrocolpopexy.

Pelvic organ prolapse (POP) is a common condition affecting over half of women above the age of 50. Sacrocolpopexy is a widely recognized surgical approach for apical prolapse, restoring the vaginal axis effectively. Despite its efficacy, complications such as bowel dysfunction and stress urinary incontinence (SUI) are common. Ileopectopexy, a newer technique utilizing the iliopectineal ligament, offers an alternative that may reduce complications while maintaining efficacy. This study compares the outcomes of robotic sacrocolpopexy and ileopectopexy in a tertiary care setting. This study retrospectively analyzed the collected database of 35 patients who underwent robotic sacrocolpopexy or ileopectopexy between 2021 and 2023. Surgeries were performed using either the Da Vinci or Hugo robotic systems. Parameters studied included console time, blood loss, complications, hospital stay, recurrence rates, and follow-up duration. Data was statistically analyzed using SPSS (IBM Corp., Armonk, NY, v28.0), with a p-value of <0.05 considered significant. Both groups had similar age distributions and presenting symptoms, most commonly complete uterine prolapse. Ileopectopexy had no complications, while sacrocolpopexy saw two vaginal lacerations. Blood loss was minimal across all cases (<100 mL). Post-operative bowel complaints were more frequent in the sacrocolpopexy group (14%), but absent in ileopectopexy. Hospital stay, console time, and additional procedures were comparable. Follow-up was longer for sacrocolpopexy (34.8 vs. 5.3 months). Both robotic sacrocolpopexy and ileopectopexy effectively managed apical prolapse with minimal blood loss and comparable hospital stays. However, ileopectopexy showed fewer bowel complications, making it a promising alternative. More extensive studies with longer follow-ups are needed to validate these findings.

Research on Obstacle-Avoidance Trajectory Planning for Drill and Anchor Materials Handling by a Mechanical Arm on a Coal Mine Drilling and Anchoring Robot.

At present, China's coal mine permanent tunneling support commonly uses mechanized drilling and anchoring equipment; there are low support efficiency, labor intensity, and other issues. In order to further improve the support efficiency and liberate productivity, this paper further researches the trajectory planning of the drilling and anchoring materials of the robotic arm for the drilling machine "grasping-carrying-loading-unloading" on the basis of the drilling and anchoring robotic system designed by the team in the previous stage. Firstly, the kinematic model of the robotic arm with material was established by improving the D-H parameter method. Then, the working space of the robotic arm with the material was analyzed using the Monte Carlo method. The singular bit-shaped region of the robotic arm was restricted, and obstacles were removed from the working space. The inverse kinematics was utilized to solve the feasible domain of the robotic arm with material. Secondly, in order to avoid blind searching, the guidance of the Bi-RRT algorithm was improved by adding the target guidance factor, and the two-way tree connection strategy for determining the feasible domain was combined with the Bi-RRT algorithm's feasible domain judgment bi-directional tree connection strategy to improve the convergence speed of the Bi-RRT algorithm. Then, in order to adapt to the dynamic environment and avoid the global planning algorithm from falling into the local minima, on the basis of the above planning methods, an improved Bi-RRT trajectory planning algorithm incorporating the artificial potential field was proposed, which takes the planned paths as the guiding potential field of the artificial potential field to make full use of the global information and avoid falling into the local minimization. Finally, a simulation environment was built in a ROS environment to compare and analyze the planning effect of different algorithms. The simulation results showed that the improved Bi-RRT trajectory planning algorithm incorporating the artificial potential field improved the optimization speed by 69.8% and shortened the trajectory length by 46.6% compared with the traditional RRT algorithm.

Usability in human-robot collaborative workspaces

AbstractThis study explores the usability of human-robot collaboration in the previously under-researched field of forestry and agroforestry. The robotic platforms used were Boston Dynamics Spot and the Agile X Bunker, the latter equipped with a movable arm. The research was conducted in an experimental robotic test park, simulating real-world scenarios relevant to forestry and agriculture. The focus of this study is on the use of these robots as collaborative robots (cobots). Usability, as a central characteristic in human-computer interaction, was evaluated using the well-established System Usability Scale (SUS). The results demonstrate the potential of these robotic systems to enhance productivity and safety, while also underscoring the importance of user-centered design in the development of collaborative tools. A key finding of this work is that successful integration of AI-driven technologies in sectors such as forestry and agriculture requires a focus on human-centered AI which includes good usability, and accessibility, emphasizing the importance of the concept of universal access.

Experiences in robotic colorectal surgery: comprehensive insights from a multi-center analysis using the Senhance Robotic System.

Robotic-assisted surgery has revolutionised minimally invasive approaches, particularly in colorectal surgery. While many single-center studies on colorectal surgeries exist in present literature, including experiences with Senhance® Robotic Systems, comprehensive multi-center studies are lacking. This study, conducted through the TransEnterix European Patient Registry ("TRUST"), aims to assess the safety and feasibility in this context. The present study explored procedural times, complications, robotic malfunction and limitations, adverse events and pain management outcomes for colorectal procedures, including sigmoid resection, right hemicolectomy and rectal surgery collected in two European centers. Data from 355 colorectal surgeries showed that the median duration of surgery was 147.2min (IQR: 124.3-183.0), the docking time was reported with a median of 3.4min (IQR: 2.0-5.4) and the console time was found at a mean of 84.4min (SD: 33.6). Despite minimal blood loss, pain scores, and robotic malfunction, 2.9% of the cases (10 instances) required conversions to either an open or laparoscopic approach. Further, most robotic limitations were attributed to limited motion (18.9%, 67 cases) and collisions (11.5%, 41 cases). Adverse events (24 cases, 6.8%) were effectively managed, with 23 instances judged completely unrelated to the robotic system. This study underscores the positive outcomes and safety profile of Senhance® Robotic Systems in colorectal surgery, contributing valuable insights for future research and clinical practice.

Robotic manipulation of cardiomyocytes to identify gap junction modifiers for arrhythmogenic cardiomyopathy.

Arrhythmogenic cardiomyopathy (ACM) is a leading cause of sudden cardiac death among young adults. Aberrant gap junction remodeling has been linked to disease-causative mutations in plakophilin-2 (PKP2). Although gap junctions are a key therapeutic target, measurement of gap junction function in preclinical disease models is technically challenging. To quantify gap junction function with high precision and high consistency, we developed a robotic cell manipulation system with visual feedback from digital holographic microscopy for three-dimensional and label-free imaging of human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). The robotic system can accurately determine the dynamic height changes in the cells' contraction and resting phases, microinject drug-treated healthy and diseased iPSC-CMs in their resting phase with constant injection depth across all cells, and deposit a membrane-impermeable dye that solely diffuses between cells through gap junctions for measuring the gap junction diffusion function. The robotic system was applied toward a targeted drug screen to identify gap junction modulators and potential therapeutics for ACM. Five compounds were found to dose-dependently enhance gap junction permeability in cardiomyocytes with PKP2 knockdown. In addition, PCO 400 (pinacidil) reduced beating irregularity in a mouse model of ACM expressing mutant PKP2 (R735X). These results highlight the utility of the robotic cell manipulation system to efficiently assess gap junction function in a relevant preclinical disease model, thus providing a technique to advance drug discovery for ACM and other gap junction-mediated diseases.

A Vision-Guided Robotic System for Safe Dental Implant Surgery.

Background: Recent advancements in dental implantology have significantly improved outcomes, with success rates of 90-95% over a 10-year period. Key improvements include enhanced preplanning processes, such as precise implant positioning, model selection, and optimal insertion depth. However, challenges remain, particularly in achieving correct spatial positioning and alignment of implants for optimal occlusion. These challenges are pronounced in patients with reduced bone substance or complex anthropometric features, where even minor misalignments can result in complications or defects. Methods: This paper introduces a vision-guided robotic system designed to improve spatial positioning accuracy during dental implant surgery. The system incorporates advanced force-feedback control to regulate the pressure applied to bone, minimizing the risk of bone damage. A preoperative CBCT scan, combined with real-time images from a robot-mounted camera, guides implant positioning. A personalized marker holder guide, developed from the initial CBCT scan, is used for patient-robot calibration. The robot-mounted camera provides continuous visual feedback of the oral cavity during surgery, enabling precise registration of the patient with the robotic system. Results: Initial experiments were conducted on a 3D-printed mandible using a personalized marker holder. Following successful patient-robot registration, the robotic system autonomously performed implant drilling. To evaluate the accuracy of the robotic-assisted procedure, further tests were conducted on 40 identical molds, followed by measurements of implant positioning. The results demonstrated improved positioning accuracy compared to the manual procedure. Conclusions: The vision-guided robotic system significantly enhances the spatial accuracy of dental implants compared to traditional manual methods. By integrating advanced force-feedback control and real-time visual guidance, the system addresses key challenges in implant positioning, particularly for patients with complex anatomical structures. These findings suggest that robotic-assisted implant surgery could offer a safer and more precise alternative to manual procedures, reducing the risk of implant misalignment and associated complications.

Construction of a prototype of the basic module of a scalable robotic system for simulation of composite surfaces for dynamic tests

The authors of the article developed a mathematical model of Stewart platform management. The angles of rotation of the servo shafts were obtained when setting various laws of motion of the mobile platform, in matrix mode. The hardware part of the prototype of the basic module of a scalable robotics system for modeling composite surfaces for dynamic tests was developed. The results of calculations of the maximum permissible load on the shafts of servos are presented. The CubeIDE settings for programming the STM32 microcontroller are given. The results of software development for the control of this prototype were obtained, namely, a library for controlling 6 servo drives under driver control was written. The problems that may arise during the above-described developments by future developers are considered, solutions to these problems are obtained. Detailed design features of this prototype are described, the control code of the servo drive is given; steps for further development of the final robotic system are considered