Error Modeling and Sensitivity Analysis of a Parallel Robot with SCARA(Selective Compliance Assembly Robot Arm) Motions

Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.

A Hybrid Brain-Computer Interface for Closed-Loop Position Control of a Robot Arm

Brain-Computer interfacing(BCI)has currently added a new dimension in assistive robotics.Existing braincomputer interfaces designed for position control applications suffer from two fundamental limitations.First,most of the existing schemes employ open-loop control,and thus are unable to track positional errors,resulting in failures in taking necessary online corrective actions.There are examples of a few works dealing with closed-loop electroencephalography(EEG)-based position control.These existing closed-loop brain-induced position control schemes employ a fixed order link selection rule,which often creates a bottleneck preventing time-efficient control.Second,the existing brain-induced position controllers are designed to generate a position response like a traditional firstorder system,resulting in a large steady-state error.This paper overcomes the above two limitations by keeping provisions for steady-state visual evoked potential(SSVEP)induced linkselection in an arbitrary order as required for efficient control and generating a second-order response of the position-control system with gradually diminishing overshoots/undershoots to reduce steady-state errors.Other than the above,the third innovation is to utilize motor imagery and P300 signals to design the hybrid brain-computer interfacing system for the said application with gradually diminishing error-margin using speed reversal at the zero-crossings of positional errors.Experiments undertaken reveal that the steady-state error is reduced to 0.2%.The paper also provides a thorough analysis of the stability of the closed-loop system performance using the Root Locus technique.

Resonance Suppression Strategy for Humanoid Robot Arm

To address the problem of resonance in the control of a robot arm,a resonance suppression strategy is proposed for a single-joint humanoid robot arm based on the proportionalresonant(PR)controller.First,an arm joint model of the humanoid robot is established.Then the influence of resonance frequency on the performance of the control system with the robot arm is analyzed.The voltage fluctuation of the drive motor caused by the changes in arm motion is recognized as the disturbance of the current loop.The PR controller has the characteristic of disturbance rejection at a specific frequency.The output fluctuation of the driving system caused by the change of arm motion state at the resonance frequency is suppressed.Therefore the output current of the inverter will not be affected by the vibration of the arm at the resonance frequency.Finally,the control system is verified by MATLAB/Simulink simulation.The simulation results demonstrate that the control strategy for the humanoid robot arm based on the PR controller can suppress the resonance of the arm effectively,improving the dynamic performance and system stability.

Anti-Windup Control Strategy of Drive System for Humanoid Robot Arm Joint

To address the problems of torque limit and controller saturation in the control of robot arm joint,an anti-windup control strategy is proposed for a humanoid robot arm,which is based on the integral state prediction under the direct torque control system of brushless DC motor. First,the arm joint of the humanoid robot is modelled. Then the speed controller model and the influence of the initial value of the integral element on the system are analyzed. On the basis of the traditional antiwindup controller,an integral state estimator is set up. Under the condition of different load torques and the given speed,the integral steady-state value is estimated. Therefore the accumulation of the speed error terminates when the integrator reaches saturation. Then the predicted integral steady-state value is used as the initial value of the regulator to enter the linear region to make the system achieve the purpose of anti-windup. The simulation results demonstrate that the control strategy for the humanoid robot arm joint based on integral state prediction can play the role of anti-windup and suppress the overshoot of the system effectively. The system has a good dynamic performance.

Design and Development of a Competitive Low-Cost Robot Arm with Four Degrees of Freedom

The main focus of this work was to design, develop and implementation of competitively robot arm with en- hanced control and stumpy cost. The robot arm was designed with four degrees of freedom and talented to accomplish accurately simple tasks, such as light material handling, which will be integrated into a mobile platform that serves as an assistant for industrial workforce. The robot arm is equipped with several servo motors which do links between arms and perform arm movements. The servo motors include encoder so that no controller was implemented. To control the robot we used Labview, which performs inverse kinematic calculations and communicates the proper angles serially to a microcontroller that drives the servo motors with the capability of modifying position, speed and acceleration. Testing and validation of the robot arm was carried out and results shows that it work properly.

Similarity comprehensive evaluation of humanoid robot arm motion

A suitable comprehensive evaluation method for similarity comprehensive evaluation of humanoid motion(mainly to robotic arm) is proposed.For different robotic arms, a static comprehensive evaluation model is established by projection pursuit evaluation based on indexes of humanoid robot arm motion in robotics and ergonomics field. Based on projection pursuit evaluation with timing information entropy and time degrees, a dynamic comprehensive evaluation method is proposed by linear weighting to each time's static model's indexes weight according to timing weighted vectors. Through comparing similarity comprehensive evaluation result based on static and dynamic comprehensive evaluation model, the results show that similarity based on dynamic comprehensive evaluation model is high. By comparing reliability, similarity and dispersion of static and dynamic comprehensive evaluation models, the results show that dynamic comprehensive evaluation result has better accuracy, stability and lower dispersion, and the result is more reasonable and real. Therefore, the dynamic comprehensive evaluation method proposed in this paper is more suitable for similarity comprehensive evaluation of humanoid robot arm motion.

Path Planning for Robotic Arms Based on an Improved RRT Algorithm

The burgeoning robotics industry has catalyzed significant strides in the development and deployment of industrial and service robotic arms, positioning path planning as a pivotal facet for augmenting their operational safety and efficiency. Existing path planning algorithms, while capable of delineating feasible trajectories, often fall short of achieving optimality, particularly concerning path length, search duration, and success likelihood. This study introduces an enhanced Rapidly-Exploring Random Tree (RRT) algorithm, meticulously designed to rectify the issues of node redundancy and the compromised path quality endemic to conventional RRT approaches. Through the integration of an adaptive pruning mechanism and a dynamic elliptical search strategy within the Informed RRT* framework, our algorithm efficiently refines the search tree by discarding branches that surpass the cost of the optimal path, thereby refining the search space and significantly boosting efficiency. Extensive comparative analysis across both two-dimensional and three-dimensional simulation settings underscores the algorithm’s proficiency in markedly improving path precision and search velocity, signifying a breakthrough in the domain of robotic arm path planning.

Modeling and Adaptive Neural Network Control for a Soft Robotic Arm With Prescribed Motion Constraints

This paper presents a dynamic model and performance constraint control of a line-driven soft robotic arm.The dynamics model of the soft robotic arm is established by combining the screw theory and the Cosserat theory.The unmodeled dynamics of the system are considered,and an adaptive neural network controller is designed using the backstepping method and radial basis function neural network.The stability of the closed-loop system and the boundedness of the tracking error are verified using Lyapunov theory.The simulation results show that our approach is a good solution to the motion constraint problem of the line-driven soft robotic arm.

基于ARM的婴幼儿催眠成长智能机器人设计

装置介绍了一种基于ARM的多种智能控制机械臂达到促进婴幼儿睡眠、心理健康成长和缓解母亲压力的效果,其结构由报警单元、烘干装置、机械臂仿真装置、摄像单元、温湿度及压力采集单元、光电传感器、婴儿床等组成。该装置由手机APP手动或自动的对六个舵机全方位的精准控制,使机械臂可以多姿态的运转并呈现仿真人手臂摇摆姿势的循环,机械臂外壳采用热感的慢回弹材料,高度仿真人手臂,为婴儿提供柔和真实的支撑。设计新颖、安全且性能强。

Motor Imagery and Error Related Potential Induced Position Control of a Robotic Arm

The paper introduces an electroencephalography(EEG) driven online position control scheme for a robot arm by utilizing motor imagery to activate and error related potential(ErrP) to stop the movement of the individual links, following a fixed(pre-defined) order of link selection. The right(left)hand motor imagery is used to turn a link clockwise(counterclockwise) and foot imagery is used to move a link forward. The occurrence of ErrP here indicates that the link under motion crosses the visually fixed target position, which usually is a plane/line/point depending on the desired transition of the link across 3D planes/around 2D lines/along 2D lines respectively. The imagined task about individual link's movement is decoded by a classifier into three possible class labels: clockwise, counterclockwise and no movement in case of rotational movements and forward, backward and no movement in case of translational movements. One additional classifier is required to detect the occurrence of the ErrP signal, elicited due to visually inspired positional link error with reference to a geometrically selected target position. Wavelet coefficients and adaptive autoregressive parameters are extracted as features for motor imagery and ErrP signals respectively. Support vector machine classifiers are used to decode motor imagination and ErrP with high classification accuracy above 80%. The average time taken by the proposed scheme to decode and execute control intentions for the complete movement of three links of a robot is approximately33 seconds. The steady-state error and peak overshoot of the proposed controller are experimentally obtained as 1.1% and4.6% respectively.

基于ARM-STM32的智能消杀作业机器人平台及终端

本文介绍了一种基于STM32的智能消杀作业机器人,其核心部件包括智能无人车载底盘、消杀喷雾模块、红外体温监测模块、装载模块、无人机追踪模块和STM32单片机,可接收来自移动平台、专业控制设备等多种平台的控制指令。该机器人实现了对公共区域的远程监控及无人化自动作业,具有自主、智能、便捷、高效的优点,有效地解放了人力,提高了工作效率,降低了工作人员的感染风险,具有良好的使用前景。

Design of a 4 DOF parallel robot arm and the firmware implementation on embedded system to transplant pot seedlings

This paper presents a firmware design and its implementation on a real time embedded system for driving a 4 DOF parallel robot arm.The firmware primarily comprised of two components to produce motion of the robot arm:a)generation of continuous position coordinates and b)generation of actuating signals.These two componentswere processed in two different microcontrollerswith a common communication bus.The position generation algorithm produced and transmitted continuous position data to the motion generation algorithm in the form of G-code strings by reading the input positionswhichwere previously stored by the user in EEPROMmemory of the microcontroller.The receipt of a handshake signal synchronized the data transmission between these components through a communication bus.An LCD display and keypad were used as human-machine interface(HMI)to communicate with the user to set the robot target coordinates.The mechanical structure of the robot arm comprised of multiple links which were actuated by steppermotors.The workspace boundary were sensed by limit switches.The kinematic equations represented the gripper position for the corresponding input joint angles.A microcontroller was used to compute kinematic equations of the robot arm with the help of motion generation algorithm to generate actuation signals for the simultaneous movement of robot joints.The kinematic equations were solved with the dual-core capability of the microcontroller using real time operating system(RTOS),which made the computation faster with an average computation time of 198μs per step.The developed firmware was implemented and tested on a 4 DOF parallel manipulator using embedded microcontrollers for continuous pickup and place of the paper pot seedlings for automating the metering of pot seedlings.The cycle time taken for pickup and dropping of each seedling was 3.5 s with a success rate of 93.3%.

Kinect-Based Motion Recognition Tracking Robotic Arm Platform

The development of artificial intelligence technology has promoted the rapid improvement of human-computer interaction. This system uses the Kinect visual image sensor to identify human bone data and complete the recognition of the operator’s movements. Through the filtering process of real-time data by the host computer platform with computer software as the core, the algorithm is programmed to realize the conversion from data to control signals. The system transmits the signal to the lower computer platform with Arduino as the core through the transmission mode of the serial communication, thereby completing the control of the steering gear. In order to verify the feasibility of the theory, the team built a 4-DOF robotic arm control system and completed software development. It can display other functions such as the current bone angle and motion status in real time on the computer operation interface. The experimental data shows that the Kinect-based motion recognition method can effectively complete the tracking of the expected motion and complete the grasping and transfer of the specified objects, which has extremely high operability.

Posture Maintenance Control of 2-Link Object By Nonprehensile Two-Cooperative-Arm Robot Without Compensating Friction

In this paper, a method to posture maintenance control of 2-link object by nonprehensile two-cooperative-arm robot without compensating friction is proposed. In details, a mathematical model of the 2-link object is firstly built. Based on the model, stable regions for holding motion of nonprehensile two-cooperative-arm robot are obtained while the 2-link object is kept stable on the robot arms with static friction. Among the obtained stable regions, the robust pairs of orientation angles of the 2-link object are found. Under the robust orientation angles, a feedback control system is designed to control the arms to maintain the 2-link object's posture while it is being held or lifted up. Finally, experimental results are shown to verify the effectiveness of the proposed method.

Monocular Visual-Inertial and Robotic-Arm Calibration in a Unifying Framework

Reliable and accurate calibration for camera,inertial measurement unit(IMU)and robot is a critical prerequisite for visual-inertial based robot pose estimation and surrounding environment perception.However,traditional calibrations suffer inaccuracy and inconsistency.To address these problems,this paper proposes a monocular visual-inertial and robotic-arm calibration in a unifying framework.In our method,the spatial relationship is geometrically correlated between the sensing units and robotic arm.The decoupled estimations on rotation and translation could reduce the coupled errors during the optimization.Additionally,the robotic calibration moving trajectory has been designed in a spiral pattern that enables full excitations on 6 DOF motions repeatably and consistently.The calibration has been evaluated on our developed platform.In the experiments,the calibration achieves the accuracy with rotation and translation RMSEs less than 0.7°and 0.01 m,respectively.The comparisons with state-of-the-art results prove our calibration consistency,accuracy and effectiveness.

A DoS Attacks Detection Aglorithm Based on Snort-BASE for Robotic Arm Control Systems

In response to the frequent safety accidents of industrial robots, this paper designs and implements a safety detection system for robot control. It can perform real-time security detection of robot operations on industrial production lines to improve the security and reliability of robot control systems. This paper designs and implements a robot control system based Snort-BASE for real-time online detection of DoS attacks. The system uses a six-degree-of-freedom robotic arm as an example, uses Snort to record the network communication data of the robot arm control system in real time, and filters the network traffic through self-defined rules, and then uses the BASE analysis platform to achieve security analysis of the network traffic. The solution verifies the effectiveness of online real-time detection of attacks and visualisation of attack records by designing simulated robotic arm and real robotic arm attack experiments respectively, thus achieving the security of network communication of the robot remote control system.

Development and Proof-of-Concept Study of a Novel Intraoperative Surgical Planning Tool for Robotic Arm-Assisted Total Knee Arthroplasty

Background: Intraoperative surgical planning tools (ISPTs) used in current-generation robotic arm-assisted total knee arthroplasty (RTKA) systems (such as Navio® and MAKO®) involve employment of postoperative passive joint balancing. This results in improper ligament tension, which may negatively impact joint stability, which, in turn, may adversely affect patient function after TKA. Methods: A simulation-enhanced ISPT (SEISPT) that provides insights relating to postoperative active joint mechanics was developed. This involved four steps: 1) validation of a multi-body musculoskeletal model;2) optimization of the validated model;3) use of the validated and optimized model to derive knee performance equations (KPEs), which are equations that relate implant component characteristics to implant component biomechanical responses;and 4) optimization of the KPEs with respect to these responses. In a proof-of-concept study, KPEs that involved two com- ponent biomechanical responses that have been shown to strongly correlate with poor proprioception (a common patient complaint post-TKA) were used to calculate optimal positions and orientations of the femoral and tibial components in the TKA design implanted in one subject (as reported in a publicly-available dataset). Results: The differences between the calculated implant positions and orientations and the corresponding achieved values for the implant components in the subject were not similar to component position and orientation errors reported in biomechanical literature studies involving Navio® and MAKO®. Also, we indicate how SEISPT could be incorporated into the surgical workflow of Navio® with minimal disruption and increase in cost. Conclusion: SEISPT is a plausible alternative to current-gen- eration ISPTs.