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。

Residual Vibration Reduction of High-Speed Pick-and-Place Parallel Robot Using Input Shaping

Because of their elastic links and joints,high-speed parallel robots for pick-and-place operations inevitably suffer from residual vibrations that significantly degrade their positioning accuracy.An effective approach based on the input shaping technique is presented in this paper for suppressing the residual vibration in these parallel robots.After addressing the design principle of an input shaper for a parallel robot with flexible actuated joints,a robust optimal input shaper is developed by considering the configuration-dependent flexible modes and minimizing the maximum percentage of residual vibration at the end-effector.The input shaper allows a good overall performance to be achieved throughout the entire workspace.Experimental results on a 4-DOF SCARA-type parallel robot show that the residual vibration of the end-effector is dramatically reduced and the dynamic positioning accuracy of the robot significantly improved.

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。

Neuromorphic circuits based on memristors: endowing robots with a human-like brain

Robots are widely used,providing significant convenience in daily life and production.With the rapid development of artificial intelligence and neuromorphic computing in recent years,the realization of more intelligent robots through a pro-found intersection of neuroscience and robotics has received much attention.Neuromorphic circuits based on memristors used to construct hardware neural networks have proved to be a promising solution of shattering traditional control limita-tions in the field of robot control,showcasing characteristics that enhance robot intelligence,speed,and energy efficiency.Start-ing with introducing the working mechanism of memristors and peripheral circuit design,this review gives a comprehensive analysis on the biomimetic information processing and biomimetic driving operations achieved through the utilization of neuro-morphic circuits in brain-like control.Four hardware neural network approaches,including digital-analog hybrid circuit design,novel device structure design,multi-regulation mechanism,and crossbar array,are summarized,which can well simulate the motor decision-making mechanism,multi-information integration and parallel control of brain at the hardware level.It will be definitely conductive to promote the application of memristor-based neuromorphic circuits in areas such as intelligent robotics,artificial intelligence,and neural computing.Finally,a conclusion and future prospects are discussed.

Treatment of hemolymphangioma by robotic surgery: A case report

BACKGROUND Hemolymphangioma of the jejunum is rare and lacks clinical specificity,and can manifest as gastrointestinal bleeding,abdominal pain,and intestinal obstruction.Computed tomography,magnetic resonance imaging,and other examinations show certain characteristics of the disease,but lack accuracy.Although capsule endoscopy and enteroscopy make up for this deficiency,the diagnosis also still re-quires pathology.CASE SUMMARY A male patient was admitted to the hospital due to abdominal distension and abdominal pain,but a specific diagnosis by computed tomography examination was not obtained.Partial resection of the small intestine was performed by robotic surgery,and postoperative pathological biopsy confirmed the diagnosis of hemo-lymphangioma.No recurrence in the follow-up examination was observed.CONCLUSION Robotic surgery is an effective way to treat hemolymphangioma through minima-lly invasive techniques under the concept of rapid rehabilitation.

Summarizing the evidence for robotic-assisted bladder neck reconstruction: Systematic review of patency and incontinence outcomes

Objective:Bladder neck contracture and vesicourethral anastomotic stenosis are difficult to manage endoscopically,and open repair is associated with high rates of incontinence.In recent years,there have been increasing reports of robotic-assisted bladder neck reconstruction in the literature.However,existing studies are small,heterogeneous case series.The objective of this study was to perform a systematic review of robotic-assisted bladder neck reconstruction to better evaluate patency and incontinence outcomes.Methods:We performed a systematic review of PubMed from first available date to May 2023 for all studies evaluating robotic-assisted reconstructive surgery of the bladder neck in adult men.Articles in non-English,author replies,editorials,pediatric-based studies,and reviews were excluded.Outcomes of interest were patency and incontinence rates,which were pooled when appropriate.Results:After identifying 158 articles on initial search,we included only ten studies that fit all aforementioned criteria for robotic-assisted bladder neck reconstruction.All were case series published from March 2018 to March 2022 ranging from six to 32 men,with the median follow-up of 5e23 months.A total of 119 patients were included in our analysis.A variety of etiologies and surgical techniques were described.Patency rates ranged from 50%to 100%,and pooled patency was 80%(95/119).De novo incontinence rates ranged from 0%to 33%,and pooled incontinence was 17%(8/47).Our findings were limited by small sample sizes,relatively short follow-ups,and heterogeneity between studies.

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

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.

Assistive Robotics for Upper Limb Physical Rehabilitation:A Systematic Review and Future Prospects

Physical assistive robotics are oriented to support and improve functional capacities of people.In physical rehabilitation,robots are indeed useful for functional recovery of affected limb.However,there are still open questions related to technological aspects.This work presents a systematic review of upper limb rehabilitation robotics in order to analyze and establish technological challenges and future directions in this area.A bibliometric analysis was performed for the systematic literature review.Literature from the last six years,conducted between August 2020 and May 2021,was reviewed.The methodology for the literature search and a bibliometric analysis of the metadata are presented.After a preliminary search resulted in 820 articles,a total of 66 articles were included.A concurrency network and bibliographic analysis were provided.And an analysis of occurrences,taxonomy,and rehabilitation robotics reported in the literature is presented.This review aims to provide to the scientific community an overview of the state of the art in assistive robotics for upper limb physical rehabilitation.The literature analysis allows access to a gap of unexplored options to define the technological prospects applied to upper limb physical rehabilitation robotics.

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.