Modeling Open Software Architectures of Robot Controllers: A Brief Survey of Modeling Methods and Developing Methods

Openness is one of the features of modern robot controllers. Although many modeling technologies have been discussed to model and develop open robot controllers, the focus is always on modeling methodology. The relation between the former and the latter is usually ignored. According to the general software architecture of open robot controllers, this paper discusses modeling and developing methods. And the relation between the typical ones is analyzed.

Open Architecture of Single-processor Real-time Robot Control System Based on Windows NT

This paper introduces the architecture and implementation of an industrial robot control system based on Windows NT. This robot control system, which is based on a single-processor structure, can run on general industrial computers. Owing to using Windows NT's real-time extension RTX, the control system can achieve good realtime performance and friendly user interface in one general-purpose operating system. A three layer hierarchical architecture of control software is proposed to make the system more scalable and flexible. Furthermore a communication and configuration system is implemented to enable modules to communicate with each other, which make the control system scalable and flexible.

The Modeling Strategies for Open Software Architecture of Robot Controller

Although the modeling technologies for open robot controllers have been discussed widely, not much literature is devoted to the actual general modeling principles and strategies. The reason is that many researches focus on specific application fields. This paper accommodates for this lacuna and provides some general modeling principles and strategies. At last, the actual new modeling method Hierarchical Object Oriented Petri net (HOONet) which has been proved to be an effective modeling methodology, is used to illustrate the modeling strategies.

Mobile Detecting Robot Controlled by Smartphone Based on iOS

The proposed scheme is composed of a smartphone, a vehicle equipped with Wi-Fi module and an IPCam working as a detecting robot to explore the unknown environment. Besides, another vehicle equipped with Wi-Fi module is also developed as a trunk robot to extend the detecting range. On the other hand, these vehicles are designed to be driven by the smartphone based on iOS (an iPod Touch in the experiments) via Wi-Fi module along with some proper designs of control circuit mounted on the vehicles. By the audio-visual feedback signals from IPCam, the real-time scenario from the detecting area not only can be shown on the screen of the smartphone but also provides the information of the detected environment in order to guide the robot. Two control approaches were provided in the proposed control scheme, the touch-panel control and the smartphone-status control, to drive the vehicles with the help of visual feedback on the screen of the smartphone. Moreover, the trajectories of the robots were also recorded for further applications. Some experimental results are given to validate the satisfactory performance of the proposed control scheme.

Robot Control System Based on Electrooculography and Electromyogram

This paper describes a man-machine interface system using EOG and EMG. A manipulator control system using EOG and EMG is developed according to EOG and EMG. With the eye movement, the system enabled us to control a manipulator. EOG is using for moving the robot joint angles and EMG is using for object grasping. The EOG and EMG discrimination method is used to control the robot. The robot arm joint movements are determined by the EOG discrimination method where the polarity of eye gaze motion signals in each Ch1 and Ch2. The EMG discrimination method is used to control arm gripper to grasp and release the target object. In the robot control experiment, we are successfully control the uArmTM robot by using both EOG and EMG discrimination method as the control input. This control system brings the feasibility of man-machine interface for elderly person and handicapped person.

Adaptive Robust Control with Leakage-Type Control Law for Trajectory Tracking of Exoskeleton Robots

This paper investigates the trajectory following problem of exoskeleton robots with numerous constraints. However, as a typical nonlinear system with variability and parameter uncertainty, it is difficult to accurately achieve the trajectory tracking control for exoskeletons. In this paper, we present a robust control of trajectory tracking control based on servo constraints. Firstly, we consider the uncertainties (e.g., modelling errors, initial condition deviations, structural vibrations, and other unknown external disturbances) in the exoskeleton system, which are time-varying and bounded. Secondly, we establish the dynamic model and formulate a close-loop connection between the dynamic model and the real world. Then, the trajectory tracking issue is regarded as a servo constraint problem, and an adaptive robust control with leakage-type adaptive law is proposed with the guaranteed Lyapunov stability. Finally, we conduct numerical simulations to verify the performance of the proposed controller.

天玑骨科机器人TiRobot Recon导航系统使用风险关键控制点确定及运维管理体系应用效果分析

目的:构建天玑骨科机器人TiRobot Recon导航系统风险控制点确定及运维管理体系(以下简称风险控制运维管理体系)并分析应用效果,为提高天玑骨科机器人临床服务效果和质量提供理论指导与参考。方法:通过查阅文献、总结临床实践经验等方式明确天玑骨科机器人TiRobot Recon导航系统风险关键控制点,据此构建风险控制运维管理体系,比较该体系实施前(2022年1月~2022年12月)与实施后(2023年1月~2023年12月)对天玑骨科机器人TiRobot Recon导航系统的管理效果。结果:实施风险控制运维管理体系后,天玑骨科机器人TiRobot Recon导航系统日均使用时间、预期目标达标率、系统风险事件上报准确性、风险预警及时性和风险事件数据规范性均高于实施前,系统故障待机时间和故障率低于实施前,差异有统计学意义(t=6.956、9.656、5.415、4.678、3.711、3.354、5.229,P<0.05);实施分线控制运维管理体系后,天玑骨科机器人TiRobot Recon导航系统的人员日常养护、使用前检查、使用后清洁、系统操作、故障应对、紧急处理等操作熟练度评分均高于实施前,差异有统计学意义(t=4.225、2.399、2.385、2.597、2.421、3.560,P<0.05)。结论:采用风险控制运维管理体系可提高天玑骨科机器人TiRobot Recon导航系统的使用效果,强化人员操作熟练度,临床应用优势明显,具有应用价值。

Development of a Multi-DOF Robotic Controller for Academic Purposes

This article presents the development of a robotic controller for technical training, academic teaching, and research. The controller was designed to interact from 1 to 6 DOF （degrees of freedom） serial robotic arms, actuated by brushed DC （direct current） servomotors equipped with incremental encoders. Controller architecture is based on four components： a processor, a reconfigurable FPGA （field-programmable gate array）, measurement I/O hardware and software. Functionality of the robotic controller has been proved by means of the interaction with an SCARA （selective compliance assembly robot arm）. The proposed controller presents the potential to teach technical courses （like robotics, control, electronics and programming） and to implement and validate advanced control algorithms.

Observer Based Control for a Class of Systems with Output Deadzone Nonlinearity

In this paper, a combination of model based adaptive design along with adaptive linear output feedback controller is used to compensate for robotic manipulator with output deadzone nonlinearity. The deadzone dynamics are utilized to adaptively estimate the deadzone parameter and a switching function is designed to eliminate the error produced in the adaptive observer dynamics. The overall design of the closed loop system ensures stability in the BIBO criterion.

Design of Robotic Visual Servo Control Based on Neural Network and Genetic Algorithm

A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.

High-speed Nonsingular Terminal Switched Sliding Mode Control of Robot Manipulators

This paper proposes a high-speed nonsingular terminal switched sliding mode control(HNT-SSMC) strategy for robot manipulators. The proposed approach enhances the control system performance by switching among appropriate sliding mode controllers according to different control demands in different regions of the state space. It is shown that the highspeed nonsingular terminal switched sliding mode(HNT-SSM)which is the representation of different control demands and enforced by the HNT-SSMC has the property of global highspeed convergence compared with the nonsingular fast terminal sliding mode(NFTSM), and provides the global non-singularity.The simulation study of an application example is carried out to validate the effectiveness of the proposed strategy.

A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models

Taking advantage of their inherent dexterity,robotic arms are competent in completing many tasks efficiently.As a result of the modeling complexity and kinematic uncertainty of robotic arms,model-free control paradigm has been proposed and investigated extensively.However,robust model-free control of robotic arms in the presence of noise interference remains a problem worth studying.In this paper,we first propose a new kind of zeroing neural network(ZNN),i.e.,integration-enhanced noise-tolerant ZNN(IENT-ZNN)with integration-enhanced noisetolerant capability.Then,a unified dual IENT-ZNN scheme based on the proposed IENT-ZNN is presented for the kinematic control problem of both rigid-link and continuum robotic arms,which improves the performance of robotic arms with the disturbance of noise,without knowing the structural parameters of the robotic arms.The finite-time convergence and robustness of the proposed control scheme are proven by theoretical analysis.Finally,simulation studies and experimental demonstrations verify that the proposed control scheme is feasible in the kinematic control of different robotic arms and can achieve better results in terms of accuracy and robustness.

A Back-stepping Based Trajectory Tracking Controller for a Non-chained Nonholonomic Spherical Robot

Spherical robot has good static and dynamic stability, which provides it with strong viability in hostile environment, but the lack of effective control methods has hindered its application and development. This article deals with the dynamic trajectory tracking problem of the spherical robot BHQ-2 designed for unmanned environment exploration. The dynamic model of the spherical robot is established with a simplified Boltzmann-Hamel equation, based on which a trajectory tracking controller is designed by using the back-stepping method. The convergence of the controller is proved with the Lyapunov stability theory. Numerical simulations show that with the controller the robot can globally and asymptotically track desired trajectories, both linear and circular.

Tracking controller for robot manipulators viac omposite nonlinear feedback law

A composite nonlinear feedback tracking controller for motion control of robot manipulators is described. The structure of the controller is composed of a composite nonlinear feedback law plus full robot nonlinear dynamics compensation. The stability is carried out in the presence of friction. The controller takes advantage of varying damping ratios induced by the composite nonlinear feedback control, so the transient performance of the closed-loop is remarkably improved. Simulation results demonstrate the feasibility of the proposed method.

Multimodal Integration Processes in Plan-Based Service Robot Control

Cross-modal integration processes are essential for service robots to reliably perceive relevant parts of the partially known unstructured environment, We demonstrate how multimodal integration on different abstraction levels leads to reasonable behavior that would be difficult to achieve with unimodal approaches. Sensing and acting modalities are composed to multimodal robot skills via a fuzzy multisensor fusion approach. Single modalities constitute basic robot skills that can dynamically be composed to appropriate behavior by symbolic planning. Furthermore, multimodal integration is exploited to answer relevant queries about the partially known environment. All these approaches are successfully implemented and tested on our mobile service robot platform TASER,

Design of Industrial Robotic Controller Based on DSP

This paper describes the design of industrial robot controller based on the DSP technology. Robotic real time control is realized by PC and DSP motion control card and this method improves the performance of robotic controller. Finally this paper gives some experiment results and conclusion.

Radial basis function‐based exoskeleton robot controller development

The realisation of a model‐based controller for a robot with a higher degree of freedom requires a substantial amount of computational power.A high‐speed CPU is required to maintain a higher sampling rate.Multicore processors cannot boost the performance or reduce the execution time as the programs are sequentially structured.The neural network is a great tool to convert a sequentially structured program to an equivalent parallel architecture program.In this study,a radial basis function(RBF)neural network is developed for controlling 7 degrees of freedom of the human lower extremity exoskel-eton robot.A realistic friction model is used for modelling joint friction.High trajectory tracking accuracies have been obtained.Evidence of computational efficiency has been observed.The stability analysis of the developed controller is presented.Analysis of variance is used to assess the controller's resilience to parameter variation.To show the effectiveness of the developed controller,a comparative study was performe between the developed RBF network‐based controller and Sliding Mode Controller,Computed Tor-que Controller,Adaptive controller,Linear Quadratic Regulator and Model Reference Computed Torque Controller.

Adaptive Terminal Sliding Mode Control for Rigid Robotic Manipulators

In order to apply the terminal sliding mode control to robot manipulators,prior knowledge of the exact upper bound of parameter uncertainties,and external disturbances is necessary.However,this bound will not be easily determined because of the complexity and unpredictability of the structure of uncertainties in the dynamics of the robot.To resolve this problem in robot control,we propose a new robust adaptive terminal sliding mode control for tracking problems in robotic manipulators.By applying this adaptive controller,prior knowledge is not required because the controller is able to estimate the upper bound of uncertainties and disturbances.Also,the proposed controller can eliminate the chattering effect without losing the robustness property.The stability of the control algorithm can be easily verified by using Lyapunov theory.The proposed controller is tested in simulation on a two-degree-of-freedom robot to prove its effectiveness.

Robust adaptive tracking control of robotic systems with uncertainties

To deal with the uncertainty factors of robotic systems, a robust adaptive tracking controller is proposed. The knowledge of the uncertainty factors is assumed to be unidentified; the proposed controller can guarantee robustness to parametric and dynamics uncertainties and can also reject any bounded, immeasurable disturbances entering the system. The stability of the proposed controller is proven by the Lyapunov method. The proposed controller can easily be implemented and the stability of the closed system can be ensured; the tracking error and adaptation parameter error are uniformly ultimately bounded （UUB）. Finally, some simulation examples are utilized to illustrate the control performance.

Improved single-neuron PID controller for DC motor applied in robot system

An improved single-neuron proportional integral derivative （ PID ） controller and a new method to build the DC motor system were presented in the article. In the simulation, the robot arm is considered as an external load to DC motor. Both the motor module and the load module are crea- ted in Simulink to achieve simulation results closer to real robot system. In this way, it can well veri- fy the performance of the improved single-neuron PID controller, which is a combined controller of normal PID controller and single-neuron PID controller. Besides, an intelligent switcher can help to realize the function of choosing a better control algorithm according to motor＇ s velocity output. Sim- ulated results confirm the rapid and stable response of the improved PID controller. Moreover, the improved single-neuron PID controller has an excellent ability to overcome the load impact and su- press the jamming signals. At last, a GUI interface platform is built to make the controller easier to be applied in other robot systems.