Fuzzy Theory Based Control Method for an In-pipe Robot to Move in Variable Resistance Environment

Most of the existing screw drive in-pipe robots cannot actively adjust the maximum traction capacity, which limits the adaptability to the wide range of variable environment resistance, especially in curved pipes. In order to solve this problem, a screw drive in-pipe robot based on adaptive linkage mechanism is proposed. The differential property of the adaptive linkage mechanism allows the robot to move without motion interference in the straight and varied curved pipes by adjusting inclining angles of rollers self-adaptively. The maximum traction capacity of the robot can be changed by actively adjusting the inclining angles of rollers. In order to improve the adaptability to the variable resistance, a torque control method based on the fuzzy controller is proposed. For the variable environment resistance, the proposed control method can not only ensure enough traction force, but also limit the output torque in a feasible region. In the simulations, the robot with the proposed control method is compared to the robot with fixed inclining angles of rollers. The results show that the combination of the torque control method and the proposed robot achieves the better adaptability to the variable resistance in the straight and curved pipes.

Unilateral self-locking mechanism for inchworm in-pipe robot

A unilateral self-locking mechanism(USM) was proposed to increase the tractive ability of the inchworm in-pipe robots for pipeline inspection.The USM was basically composed of a cam,a torsional spring and an axis.The self-locking and virtual work principles were applied to studying the basic self-locking condition of the USM.In order to make the cooperation between the crutch and telescopic mechanism more harmonical,the unlocking time of the USM was calculated.A set of parameters were selected to build a virtual model and fabricate a prototype.Both the simulation and performance experiments were carried out in a pipe with a nominal inside diameter of 160 mm.The results show that USM enables the robot to move quickly in one way,and in the other way it helps the robot get self-locking with the pipe wall.The traction of the inchworm robot can rise to 1.2 kN,beyond the limitation of friction of 0.497 kN.

Global localization of in-pipe robot based on ultra-long wave antenna array and global position system

A global localization system of in-pipe robot is introduced in this paper.Global position system(GPS)is applied to monitor the motion of robot along the whole pipeline which is equally divided intomany segments by tracking stations.The definite segment in which robot existing can be detected and thisis long-range localization.Ultra-long wave(ULW)is adopted to solve the problem of metallic shieldingand realize effective communication between inside and outside of pipeline.ULW emitter is carried byrobot.When the plant is broken or defects on pipe-wall are inspected,the robot will stop moving.Anten-na array is presented and disposed upon the definite segment to search the accurate location of robot,andthis is short-range localization.In this paper,five-antenna array is adopted and an effective linear signalfusion algorithm is presented.The localization precision reaches R < 25cm.By tests in Shengli oil field,the whole system is verified with robust solutions.

A Novel Worm-like In-Pipe Robot with the Rigid and Soft Structure

Soft in-pipe robot has good adaptability in tubular circumstances,while its rigidity is insufficient,which affects the traction performance.This paper proposes a novel worm-like in-pipe robot with a rigid and soft structure,which not only has strong traction ability but also flexible mobility in the shaped pipes.Imitating the structure features of the earthworm,the bionic in-pipe robot structure is designed including two soft anchor parts and one rigid telescopic part.The soft-supporting mechanism is the key factor for the in-pipe robot excellent performance,whose mathematical model is established and the mechanical characteristics are analyzed,which is used to optimize the structural parameters.The prototype is developed and the motion control strategy is planned.Various performances of the in-pipe robot are tested,such as the traction ability,moving velocity and adaptability.For comparative analysis,different operating scenarios are built including the horizontal pipe,the inclined pipe,the vertical pipe and other unstructured pipes.The experiment results show that the in-pipe robot is suitable for many kinds of pipe applications,the average traction is about 6.8N,the moving velocity is in the range of 9.5 to 12.7 mm/s.

A wheel-type in-pipe robot for grinding weld beads

To improve the safety and efficiency of polishing operations in circular boiler headers, a new type of wheel-drive polishing robot was developed in this study. The robot was designed to grind weld beads on the inner walls of pipes in diameter between 550 mm and 714 mm. The robot consists of a moving structure, a positioning structure, and a polishing structure. Charge coupled device （CCD） cameras and line lasers are used in the robot＇s vision system, thus the robot can be manually controlled to move, locate, and grind quickly and accurately. The experimental results showed that the robot performed well in practical applications.

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。

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。

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.

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 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.

Colorectal resections for malignancy: A pilot study comparing conventional vs freehand robot-assisted laparoscopic colectomy

BACKGROUND Laparoscopic colectomy is widely accepted as a safe operation for colorectal cancer,but we have experienced resistance to the introduction of the FreeHandffrobotic camera holder to augment laparoscopic colorectal surgery.AIM To compare the initial results between conventional and FreeHandffrobot-assisted laparoscopic colectomy in Trinidad and Tobago.METHODS This was a prospective study of outcomes from all laparoscopic colectomies per-formed for colorectal carcinoma from November 29,2021 to May 30,2022.The following data were recorded:Operating time,conversions,estimated blood loss,hospitalization,morbidity,surgical resection margins and number of nodes har-vested.All data were entered into an excel database and the data were analyzed using SPSS ver 20.0.RESULTS There were 23 patients undergoing colectomies for malignant disease:8(35%)FreeHandff-assisted and 15(65%)conventional laparoscopic colectomies.There were no conversions.Operating time was significantly lower in patients under-going robot-assisted laparoscopic colectomy(95.13±9.22 vs 105.67±11.48 min;P=0.045).Otherwise,there was no difference in estimated blood loss,nodal harvest,hospitalization,morbidity or mortality.CONCLUSION The FreeHandffrobot for colectomies is safe,provides some advantages over conventional laparoscopy and does not compromise oncologic standards in the resource-poor Caribbean setting.

An artificial systems,computational experiments and parallel execution-based surface electromyogram-driven anti-disturbance zeroing neurodynamic strategy for upper limb human-robot interaction control

In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ameliorated.Specially,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be addressed.To deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI control.The upper limb-robotic exoskeleton system is re-modelled as an artificial system.Depending on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical system.Furthermore,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and compared.Theoretical results substantiate the global convergence and robustness of the proposed controller in the presence of different external disturbances.In addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.

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.

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.