基于RobotStudio的视觉分拣打磨工作站仿真设计

为解决中小型零件混流自动化生产等问题,提出基于RobotStudio的工业机器人视觉分拣打磨工作站的仿真设计方案。根据零件的生产工艺流程,利用UG软件创建视觉分拣打磨工作站的整体布局;通过分析工作站各个模块功能,设计了各模块的结构;利用RobotStudio软件构建了工作站仿真模型。以视觉引导Smart组件和输送链跟踪仿真为例,阐述了ABB工业机器人通过视觉引导获取工件空间位姿的四元数和欧拉角的转换方法,并介绍了视觉拍照、机器人与工业相机通信等动态仿真的设置过程,以及输送链跟踪动态效果的设置方法。为实现工作站全过程仿真,设计了整体工作站逻辑,编制了仿真工作站离线程序,并将仿真工作站同步到实验平台调试验证。该设计可为智能制造生产线的设计、制造及应用提供参考。

The evolution of robotics:research and application progress of dental implant robotic systems

The use of robots to augment human capabilities and assist in work has long been an aspiration.Robotics has been developing since the 1960s when the first industrial robot was introduced.As technology has advanced,robotic-assisted surgery has shown numerous advantages,including more precision,efficiency,minimal invasiveness,and safety than is possible with conventional techniques,which are research hotspots and cutting-edge trends.This article reviewed the history of medical robot development and seminal research papers about current research progress.Taking the autonomous dental implant robotic system as an example,the advantages and prospects of medical robotic systems would be discussed which would provide a reference for future research.

基于Robotstudio的工业机器人课程教学设计与实践

阐述工业机器人实训课程教学实践,将Robotstudio软件融入课程教学中,探讨以实例项目驱动的教学内容设计,以虚实结合手段提升课堂教学效果的教学模式,从而实现教学与实践的统一。

基于Robot Studio的分类码垛仿真设计

针对工业机器人轨迹规划和自动化生产协调难度大的问题,提出一种基于Robot Studio的分类码垛仿真设计方案。使用Robot Studio软件,创建工业机器人仿真工作站。通过Smart组件的设计、I/O信号的设定、工作站逻辑的建立和程序编写等工作,最终实现工业机器人智能分类码垛操作。经过模拟仿真,结果表明:分类码垛的速度和准确率均可达到预期要求。说明该分类码垛设计方案可行,可以为实际码垛工作站的搭建和生产提供一定的现实指导。

Robotic surgery in living liver donors and liver recipients

There have been nearly 60 years since Thomas Starzl’s first liver transplant.During this period,advancements in medical technology have progressively enabled the adoption of new methods for transplantation.Among these innovations,robotic surgery has emerged in recent decades and is gradually being integrated into transplant medicine.Robotic hepatectomy and liver implantation represent significant advancements in the field of transplant surgery.The precision and minimally invasive nature of robotic surgery offer substantial benefits for both living donors and recipients.In living donors,robotic hepatectomy reduces postoperative pain,minimizes scarring,and accelerates recovery.For liver recipients,robotic liver implantation enhances surgical accuracy,leading to better graft positioning and vascular anastomosis.Robotic systems provide more precise and maneuverable control of instruments,allowing surgeons to perform complex procedures with greater accuracy and reduced risk to patients.This review encompasses publications on minimally invasive donor liver surgery,with a specific focus on robotic liver resection in transplantation,and aims to summarize current knowledge and the development status of robotic surgery in liver transplantation,focusing on liver resection in donors and graft implantation in recipients.

Managerial perspectives of scaling up robotic-assisted surgery in healthcare systems:A systematic literature review

Objectives Robotic-assisted surgery(RAS)is a minimally invasive technique practiced in multiple specialties.Standard training is essential for the acquisition of RAS skills.The cost of RAS is considered to be high,which makes it a burden for institutes and unaffordable for patients.This systematic literature review(SLR)focused on the various RAS training methods applied in different surgical specialties,as well as the cost elements of RAS,and was to summarize the opportunities and challenges associated with scaling up RAS.Methods An SLR was carried out based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses reporting guidelines.The PubMed,EBSCO,and Scopus databases were searched for reports from January 2018 through January 2024.Full-text reviews and research articles in the English language from Asia-Pacific countries were included.Articles that outlined training and costs associated with RAS were chosen.Results The most common training system is the da Vinci system.The simulation technique,which includes dry-lab,wet-lab,and virtual reality training,was found to be a common and important practice.The cost of RAS encompasses the installation and maintenance costs of the robotic system,the operation theatre rent,personnel cost,surgical instrument and material cost,and other miscellaneous charges.The synthesis of SLR revealed the challenges and opportunities regarding RAS training and cost.Conclusions The results of this SLR will help stakeholders such as decision-makers,influencers,and end users of RAS to understand the significance of training and cost in scaling up RAS from a managerial perspective.For any healthcare innovation to reach a vast population,cost-effectiveness and standard training are crucial.

Direct 4D printing of functionally graded hydrogel networks for biodegradable,untethered,and multimorphic soft robots

Recent advances in functionally graded additive manufacturing(FGAM)technology have enabled the seamless hybridization of multiple functionalities in a single structure.Soft robotics can become one of the largest beneficiaries of these advances,through the design of a facile four-dimensional(4D)FGAM process that can grant an intelligent stimuli-responsive mechanical functionality to the printed objects.Herein,we present a simple binder jetting approach for the 4D printing of functionally graded porous multi-materials(FGMM)by introducing rationally designed graded multiphase feeder beds.Compositionally graded cross-linking agents gradually form stable porous network structures within aqueous polymer particles,enabling programmable hygroscopic deformation without complex mechanical designs.Furthermore,a systematic bed design incorporating additional functional agents enables a multi-stimuli-responsive and untethered soft robot with stark stimulus selectivity.The biodegradability of the proposed 4D-printed soft robot further ensures the sustainability of our approach,with immediate degradation rates of 96.6%within 72 h.The proposed 4D printing concept for FGMMs can create new opportunities for intelligent and sustainable additive manufacturing in soft robotics.

Smart Gait:A Gait Optimization Framework for Hexapod Robots

The current gait planning for legged robots is mostly based on human presets,which cannot match the flexible characteristics of natural mammals.This paper proposes a gait optimization framework for hexapod robots called Smart Gait.Smart Gait contains three modules:swing leg trajectory optimization,gait period&duty optimization,and gait sequence optimization.The full dynamics of a single leg,and the centroid dynamics of the overall robot are considered in the respective modules.The Smart Gait not only helps the robot to decrease the energy consumption when in locomotion,mostly,it enables the hexapod robot to determine its gait pattern transitions based on its current state,instead of repeating the formalistic clock-set step cycles.Our Smart Gait framework allows the hexapod robot to behave nimbly as a living animal when in 3D movements for the first time.The Smart Gait framework combines offline and online optimizations without any fussy data-driven training procedures,and it can run efficiently on board in real-time after deployment.Various experiments are carried out on the hexapod robot LittleStrong.The results show that the energy consumption is reduced by 15.9%when in locomotion.Adaptive gait patterns can be generated spontaneously both in regular and challenge environments,and when facing external interferences.

Intuitive Human-Robot-Environment Interaction With EMG Signals:A Review

A long history has passed since electromyography(EMG)signals have been explored in human-centered robots for intuitive interaction.However,it still has a gap between scientific research and real-life applications.Previous studies mainly focused on EMG decoding algorithms,leaving a dynamic relationship between the human,robot,and uncertain environment in real-life scenarios seldomly concerned.To fill this gap,this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction(HREI)systems.The general processing framework is summarized,and three interaction paradigms,including direct control,sensory feedback,and partial autonomous control,are introduced.EMG-based intention decoding is treated as a module of the proposed paradigms.Five key issues involving precision,stability,user attention,compliance,and environmental awareness in this field are discussed.Several important directions,including EMG decomposition,robust algorithms,HREI dataset,proprioception feedback,reinforcement learning,and embodied intelligence,are proposed to pave the way for future research.To the best of what we know,this is the first time that a review of EMG-based methods in the HREI system is summarized.It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems,in which factors in human-robot interaction,robot-environment interaction,and state perception by human sensations are considered,which has never been done by previous studies.

Comment on“Robotic surgery and liver transplantation:A single-center experience of 501 robotic donor hepatectomies”

To the Editor:We read with great interest the article by Schulze et al.entitled“Robotic surgery and liver transplantation:A single-center experience of 501 robotic donor hepatectomies”[1].It is the first single-center report including over 500 fully robotic donor hepatectomies.For the donors,the overall complication rate was 6.4%(n=32).Postoperative self-limiting bleeding(0.4%)and bile leakage from the resection plane(1.8%)were rare.

Deterministic Learning-Based Neural PID Control for Nonlinear Robotic Systems

Traditional proportional-integral-derivative(PID)controllers have achieved widespread success in industrial applications.However,the nonlinearity and uncertainty of practical systems cannot be ignored,even though most of the existing research on PID controllers is focused on linear systems.Therefore,developing a PID controller with learning ability is of great significance for complex nonlinear systems.This article proposes a deterministic learning-based advanced PID controller for robot manipulator systems with uncertainties.The introduction of neural networks(NNs)overcomes the upper limit of the traditional PID feedback mechanism’s capability.The proposed control scheme not only guarantees system stability and tracking error convergence but also provides a simple way to choose the three parameters of PID by setting the proportional coefficients.Under the partial persistent excitation(PE)condition,the closed-loop system unknown dynamics of robot manipulator systems are accurately approximated by NNs.Based on the acquired knowledge from the stable control process,a learning PID controller is developed to further improve overall control performance,while overcoming the problem of repeated online weight updates.Simulation studies and physical experiments demonstrate the validity and practicality of the proposed strategy discussed in this article.

A versatile humanoid robot platform for dexterous manipulation and human-robot collaboration

Humanoid robots have attracted much attention by virtue of their compatibility with human environments.However,biped humanoids with immense promise still cannot function steadily and reliably in real-world settings in the current state.Hence,rationally combining a humanoid robot with different stable mobile platforms is a favoured solution for diverse scenarios.Here,a new versatile humanoid robot platform,aiming to provide a generic solution that can be flexibly deployed in diverse scenarios,for example,indoors and fields is presented.Versatile humanoid robot platform incorporates multimodal perception,and extensible interfaces on hardware and software,allowing it to be rapidly integrated with different mobile platforms and end-effectors,only through easyto-assemble interfaces.Additionally,the platform has achieved impressive integration,lightness,dexterity,and strength in its class,with human-like size and rich perception,targeted to have human-intelligent manipulation skills for human-engineered environments.Overall,this article elaborates on the reasoning behind the design choices,and outlines each subsystem.Lastly,the essential performance of the platform is successfully demonstrated in a set of experiments with precise and dexterous manipulation,and human–robot collaboration requirements.

Robotic complete mesocolic excision for right colon cancer:Learning curve,training,techniques,approach,platforms,and future perspectives

Colon cancer has the fifth highest incidence worldwide and has the sixth highest mortality.Compared with rectal cancer,colon cancer currently has the worst 5-year overall survival for patients with stage II and III disease.Complete mesocolic excision has been developed as a standardized and optimized surgical technique for the excision of colon cancers.This technique has traditionally been performed through an open approach since laparoscopy is generally considered technically challenging.The robotic approach has been slowly implemented for colon cancer,but the newest robotic platforms allow for a safer and optimized approach for right colon cancer.Several robotic approaches have been developed and explored.The expansion of the current robotic platform ecosystem is gradually providing new outputs in the application of the robotic approach to complete mesocolic excision.This review gains an oversight of existing literature on robotic complete mesocolic excision for right colon cancer(learning curve,training,techniques,approach,platforms,and future perspectives).

Long Duration Coverage Control of Multiple Robotic Surface Vehicles Under Battery Energy Constraints

Dear Editor,This letter addresses long duration coverage problem of multiple robotic surface vehicles(RSVs) subject to battery energy constraints,in addition to uncertainties and disturbances. An anti-disturbance energy-aware control method is proposed for performing coverage task of RSVs. Firstly, a centroidal Voronoi tessellation(CVT) is used to optimize the partition of the given coverage area.

Simulation Analysis of Deformation Control for Magnetic Soft Medical Robots

Dear Editor,This letter presents a biocompatible cross-shaped magnetic soft robot and investigates its deformation mode control strategy through COMSOL modeling and simulation.Magnetic soft robots offer novel avenues for precise treatment within intricate regions of the human body.

Robotic management of urinary fistula

Objectives:To highlight critical preoperative and intraoperative considerations in approaching fistula repair robotically.Methods:A search of the literature was conducted to identify relevant articles pertaining to robotic management of urinary fistulae.Results:Fistulae of the genitourinary tract can be a challenging dilemma for urologists,as definitive management may require surgical intervention.Pathogenesis of both enteric and non-enteric fistulae are multifactorial,and successful repair hinges on the meticulous perioperative evaluation,planning,and execution.Traditional open techniques can subject patients to increased morbidity and prolonged hospitalizations.Since its introduction,the robotic surgical platform has continued to expand its indications.Its three-dimensional visualization and tremor free wristed instrument movements have made the robotic platform an attractive option for genitourinary fistula reconstruction.Conclusion:Robotic management of complex urinary fistulae is feasible in expert hands;more studies are needed to define its role in the treatment algorithm of this devastating conditions.

Robotic versus laparoscopic surgery for sporadic benign insulinoma:Short-and long-term outcomes

Background:Minimally invasive surgery is the optimal treatment for insulinoma.The present study aimed to compare short-and long-term outcomes of laparoscopic and robotic surgery for sporadic benign insulinoma.Methods:A retrospective analysis of patients who underwent laparoscopic or robotic surgery for insulinoma at our center between September 2007 and December 2019 was conducted.The demographic,perioperative and postoperative follow-up results were compared between the laparoscopic and robotic groups.Results:A total of 85 patients were enrolled,including 36 with laparoscopic approach and 49 with robotic approach.Enucleation was the preferred surgical procedure.Fifty-nine patients(69.4%)underwent enucleation;among them,26 and 33 patients underwent laparoscopic and robotic surgery,respectively.Robotic enucleation had a lower conversion rate to laparotomy(0 vs.19.2%,P=0.013),shorter operative time(102.0 vs.145.5 min,P=0.008)and shorter postoperative hospital stay(6.0 vs.8.5 d,P=0.002)than laparoscopic enucleation.There were no differences between the groups in terms of intraoperative blood loss,the rates of postoperative pancreatic fistula and complications.After a median follow-up of 65 months,two patients in the laparoscopic group developed a functional recurrence and none of the patients in the robotic group had a recurrence.Conclusions:Robotic enucleation can reduce the conversion rate to laparotomy and shorten operative time,which might lead to a reduction in postoperative hospital stay.

Multimode Design and Analysis of an Integrated Leg-Arm Quadruped Robot with Deployable Characteristics

To improve locomotion and operation integration, this paper presents an integrated leg-arm quadruped robot(ILQR) that has a reconfigurable joint. First, the reconfigurable joint is designed and assembled at the end of the legarm chain. When the robot performs a task, reconfigurable configuration and mode switching can be achieved using this joint. In contrast from traditional quadruped robots, this robot can stack in a designated area to optimize the occupied volume in a nonworking state. Kinematics modeling and dynamics modeling are established to evaluate the mechanical properties for multiple modes. All working modes of the robot are classified, which can be defined as deployable mode, locomotion mode and operation mode. Based on the stability margin and mechanical modeling, switching analysis and evaluation between each mode is carried out. Finally, the prototype experimental results verify the function realization and switching stability of multimode and provide a design method to integrate and perform multimode for quadruped robots with deployable characteristics.

An Automatic Implementation of Oropharyngeal Swab Sampling for Diagnosing Respiratory Infectious Diseases via Soft Robotic End-Effectors

The most widely adopted method for diagnosing respiratory infectious diseases is to conduct polymerase chain reaction(PCR)assays on patients’respiratory specimens,which are collected through either nasal or oropharyngeal swabs.The manual swab sampling process poses a high risk to the examiner and may cause false-negative results owing to improper sampling.In this paper,we propose a pneumatically actuated soft end-effector specifically designed to achieve all of the tasks involved in swab sampling.The soft end-effector utilizes circumferential instability to ensure grasping stability,and exhibits several key properties,including high load-to-weight ratio,error tolerance,and variable swab-tip stiffness,leading to successful automatic robotic oropharyngeal swab sampling,from loosening and tightening the transport medium tube cap,holding the swab,and conducting sampling,to snapping off the swab tail and sterilizing itself.Using an industrial collaborative robotic arm,we integrated the soft end-effector,force sensor,camera,lights,and remote-control stick,and developed a robotic oropharyngeal swab sampling system.Using this swab sampling system,we conducted oropharyngeal swab-sampling tests on 20 volunteers.Our Digital PCR assay results(RNase P RNA gene absolute copy numbers for the samples)revealed that our system successfully collected sufficient numbers of cells from the pharyngeal wall for respiratory disease diagnosis.In summary,we have developed a pharyngeal swab-sampling system based on an“enveloping”soft actuator,studied the sampling process,and imple-mented whole-process robotic oropharyngeal swab-sampling.

Disorder-to-order transition induced by spontaneous cooling regulation in robotic active matter

In classical matter systems, typical phase-transition phenomena usually stem from changes in state variables, such as temperature and pressure, induced by external regulations such as heat transfer and volume adjustment. However, in active matter systems, the self-propulsion nature of active particles endows the systems with the ability to induce unique collectivestate transitions by spontaneously regulating individual properties to alter the overall states. Based on an innovative robot-swarm experimental system, we demonstrate a field-driven active matter model capable of modulating individual motion behaviors through interaction with a recoverable environmental resource field by the resource perception and consumption.In the simulated model, by gradually reducing the individual resource-conversion coefficient over time, this robotic active matter can spontaneously decrease the overall level of motion, thereby actively achieving a regulation behavior like the cooling-down control. Through simulation calculations, we discover that the spatial structures of this robotic active matter convert from disorder to order during this process, with the resulting ordered structures exhibiting a high self-adaptability on the geometry of the environmental boundaries.