Multi-joint Robot Research Articles

Improvement of Torque according to the Movement Path of a Four-axis Multi-joint Robot

Improvement of Torque according to the Movement Path of a Four-axis Multi-joint Robot

Adaptive Fault-Tolerant Tracking Control for Multi-Joint Robot Manipulators via Neural Network-Based Synchronization.

In this paper, adaptive fault-tolerant control for multi-joint robot manipulators is proposed through the combination of synchronous techniques and neural networks. By using a synchronization technique, the position error at each joint simultaneously approaches zero during convergence due to the constraints imposed by the synchronization controller. This aspect is particularly important in fault-tolerant control, as it enables the robot to rapidly and effectively reduce the impact of faults, ensuring the performance of the robot when faults occur. Additionally, the neural network technique is used to compensate for uncertainty, disturbances, and faults in the system via online updating. Firstly, novel robust synchronous control for a robot manipulator based on terminal sliding mode control is presented. Subsequently, a combination of the novel synchronous control and neural network is proposed to enhance the fault tolerance of the robot manipulator. Finally, simulation results for a 3-DOF robot manipulator are presented to demonstrate the effectiveness of the proposed controller in comparison to traditional control techniques.

Topology-preserved distorted space path planning

Purpose Fast obstacle avoidance path planning is a challenging task for multijoint robots navigating through cluttered workspaces. This paper aims to address this issue by proposing an improved path-planning method based on the distorted space (DS) method, specifically designed for high-dimensional complex environments. Design/methodology/approach The proposed method, termed topology-preserved distorted space (TP-DS) method, mitigates the limitations of the original DS method by preserving space topology through elastic deformation. By applying distinct spring constants, the TP-DS autonomously shrinks obstacles to microscopic areas within the configuration space, maintaining consistent topology. This enhancement extends the application scope of the DS method to handle complex environments effectively. Findings Comparative analysis demonstrates that the proposed TP-DS method outperforms traditional methods regarding planning efficiency. Successful obstacle avoidance tasks in the cluttered workspace validate its applicability on a physical 6-DOF manipulator, highlighting its potential for industrial implementations. Originality/value The novel TP-DS method generates a topology-preserved collision-free space by leveraging elastic deformation and shows significant capability and efficiency in planning obstacle-avoidance paths in complex application scenarios.

COLLECT AND PREPARE DATASET FROM HUMAN-DEMONSTRATIONS OF SIMPLE MANIPULATION TASKS USING XARM7 ROBOTIC ARM FOR TRAINING BEHAVIOUR CLONING ALGORITHM

The goal of the study is to understand what data structure is necessary to teach a robot to perform simple manipulation tasks. Training will take place thanks to Imitation learning, using the behavior cloning algorithm. Imitation learning is extremely useful for training any robotic system, especially with multi-jointed robots. This approach allows you to avoid writing complex and cumbersome heuristic algorithms. Heuristic algorithms often contain many hyperparameters that must be chosen empirically. Imitation learning algorithms allow you to develop an End-to-End policy from the collected data, which simplifies the system and increases its reliability. In the realm of training robotic systems through Imitation Learning, the criticality of data collection cannot be overstated. The efficacy of the Behavior Cloning algorithm hinges on the quality and speed at which data is gathered. Properly curated and swiftly acquired datasets serve as the bedrock for training algorithms that emulate human behavior, allowing the robot to seamlessly replicate intricate manipulations. The efficiency of data gathering is paramount in addressing the challenges posed by the dynamic nature of real-world environments. Swift adaptation to varying conditions and unforeseen scenarios necessitates a data collection process that is not only rapid but also comprehensive. A well-curated dataset not only expedites the training process but also enhances the model's adaptability and robustness in real-world applications. In conclusion, the success of Imitation Learning algorithms, particularly those underpinned by the Behavior Cloning approach, is contingent on the meticulous and expeditious gathering of data. This underscores the importance of streamlined data collection processes, ensuring that the resultant models are not only accurate but also capable of navigating the complexities of diverse and dynamic environments. Fastidious attention to data gathering is imperative to ensure a diverse and representative dataset. The xArm7 robot, in collaboration with the Realsense D435 camera, serves as an ideal synergy for capturing a myriad of movements and scenarios. The precision of data collection directly influences the algorithm's ability to generalize, making it adept at handling a spectrum of manipulation tasks.

Variable Time-Step Physics Engine with Continuous Compliance Contact Model for Optimal Robotic Grinding Trajectory Planning.

In the transition from virtual environments to real-world applications, the role of physics engines is crucial for accurately emulating and representing systems. To address the prevalent issue of inaccurate simulations, this paper introduces a novel physics engine uniquely designed with a compliant contact model designed for robotic grinding. It features continuous and variable time-step simulations, emphasizing accurate contact force calculations during object collision. Firstly, the engine derives dynamic equations considering spring stiffness, damping coefficients, coefficients of restitution, and external forces. This facilitates the effective determination of dynamic parameters such as contact force, acceleration, velocity, and position throughout penetration processes continuously. Secondly, the approach utilizes effective inertia in developing the contact model, which is designed for multi-jointed robots through pose transformation. The proposed physics engine effectively captures energy conversion in scenarios with convex contact surface shapes through the application of spring dampers during collisions. Finally, the reliability of the contact solver in the simulation was verified through bouncing ball experiments and robotic grinding experiments under different coefficients of restitution. These experiments effectively recorded the continuous variations in parameters, such as contact force, verifying the integral stability of the system. In summary, this article advances physics engine technology beyond current geometrically constrained contact solutions, enhancing the accuracy of simulations and modeling in virtual environments. This is particularly significant in scenarios wherein there are constant changes in the outside world, such as robotic grinding tasks.

Adaptive radial basis function neural network sliding mode control of robot manipulator based on improved genetic algorithm

ABSTRACT Since the trajectory-tracking control performance of multi-joint robot manipulator may be degraded due to modeling errors and external disturbances, this paper designs a new adaptive robot manipulator trajectory tracking control method through improved genetic algorithm and radial basis function neural network sliding mode control (IGA-RBFNNSMC). Firstly, the genetic algorithm (GA) is improved by establishing superior populations centered on individuals with high fitness values and selecting individuals in the superior populations for crossover and variation. Secondly, the improved genetic algorithm (IGA) is used for the optimization of the center vector and width vector of the Gaussian basis function in radial basis function (RBF) neural network. Then, based on the dynamics model of the robot manipulator, the modeling errors are approximated by RBF neural network and eliminated by sliding mode control (SMC), and the Lyapunov theorem is used to prove the stability and convergence of the control system. Finally, a two-joint robot manipulator is taken as the research objective and the simulation results show that IGA can significantly reduce the solution time on the basis of guaranteed accuracy and IGA-RBFNNSMC can make the trajectory tracking control accurate and more efficient, which proves the effectiveness of the proposed control method.

Barrier-Based Adaptive Line-of-Sight 3-D Path-Following System for a Multijoint Robotic Fish With Sideslip Compensation.

This article proposes a novel barrier-based adaptive line-of-sight (ALOS) three-dimensional (3-D) path-following system for an underactuated multijoint robotic fish. The framework of the developed path-following system is established based on a detailed dynamic model, including a barrier-based ALOS guidance strategy, three integrated inner-loop controllers, and a nonlinear disturbance observer (NDOB)-based sideslip angle compensation, which is employed to preserve a reliable tracking under a frequently varying sideslip angle of the robotic fish. First, a barrier-based convergence strategy is proposed to deal with probable along-track error disruption and suppress the error within a manageable range. Meanwhile, an improved adaptive guidance scheme is adopted with an appropriate look-ahead distance. Afterward, a novel NDOB-based sideslip angle compensation is put forward to identify the varying sideslip angle independent of speed estimation. Subsequently, inner-loop controllers are intended for regulation about the controlled references, including a super-twisting sliding-mode control (STSMC)-based speed controller, a global fast terminal sliding-mode control (GFTSMC)-based heading controller, and a GFTSMC-based depth controller. Finally, simulations and experiments with quantitative comparison in 3-D linear and helical path following are presented to verify the effectiveness and robustness of the proposed system. This path-following system provides a solid foundation for future marine autonomous cruising of the underwater multijoint robot.

Design and Ground Performance Evaluation of a Multi-Joint Wheel-Track Composite Mobile Robot for Enhanced Terrain Adaptability

The tracked-wheeled mobile robot has gained significant attention in military, agricultural, construction, and other fields due to its exceptional mobility and off-road capabilities. Therefore, it is an ideal choice for reconnaissance and exploration tasks. In this study, we proposed a multi-jointed tracked-wheeled compound mobile robot that can overcome various terrains and obstacles. Based on the characteristics of multi-jointed robots, we designed two locomotion modes for the robot to climb stairs and established the kinematics/dynamics equations for its land movement. We evaluated the robot’s stability during slope climbing, its static stability during stair climbing, and its ability to cross trenches. Based on our evaluation results, we determined the key conditions for the robot to overcome obstacles, the maximum height it can climb stairs, and the maximum width it can cross trenches. Additionally, we developed a simulation model to verify the robot’s performance in different terrains and the reliability of its stair-climbing gait. The simulation results demonstrate that our multi-jointed tracked-wheeled compound mobile robot exhibits excellent reliability and adaptability in complex terrain, indicating broad application prospects in various fields and space missions.

Dynamics Analysis and Deep Learning-Based Fault Diagnosis of Defective Rolling Element Bearing on the Multi-Joint Robot

Industrial robots typically perform a variety of tasks and occupy critical positions in modern manufacturing fields. When certain failures occur in the internal structures of robots, it tends to result in significant financial loss and the consumption of human resources. As a result, timely and effective fault diagnosis is critical to ensuring the safe operation of robots. Deep learning-based methods are currently being widely used by researchers to address some shortcomings of traditional methods. However, due to realistic factor limitations, few researchers take the failure pattern of rotating machinery and the location of fault joints into account at the same time, so the fault types of multi-joint robots are not thoroughly investigated. In this case, we proposed a dynamic simulation method that considers the effects of bearing failures at various faulty joint locations and makes it possible to investigate more possible failure cases of multi-joint robots. In addition, we used LSTM and DCNN to perform staged fault diagnosis tasks, allowing us to gradually locate faulty joints and investigate detailed failure forms. According to the experimental results, distinguishable vibration signals corresponding to various fault states are successfully obtained, and our implemented algorithms are validated for their advanced performance in diagnosis tasks via comparative experiments.

Fault-Tolerant Control of Multi-Joint Robot Based on Fractional-Order Sliding Mode

In this paper, the problem of fault-tolerant control of actuators for multi-joint robots is studied. Aiming at the jitter problem in the design of fault-tolerant control law for conventional sliding mode controllers (SMC), a controller design method based on fractional-order sliding mode (FSMC) theory is proposed. At first, the mathematical model of the multi-joint robot is established and the fractional-order sliding mode surface is constructed according to the mathematical model. Then, the robust control law is designed based on the Lyapunov function. Finally, the experiments are carried out. Compared with the conventional sliding mode control, the experimental results show that the multi-joint robot is more stable under the control of fractional-order sliding mode, and it can achieve almost no jitter while tracking the reference. The steady-state error for joint1 and joint2 could reach 0.073 radians under the control of SMC, while it is 0.015 radians under the control of FSMC. The steady-state error data indicate that the fluctuation amplitude under FSMC is five times smaller than SMC for the end part of the multi-joint robot under actuator gain faults. The regulation time for joint1 and joint2 is about 0.11 s under the control of SMC, and it is around 0.04 s for FSMC. The regulation time is reduced to one of three or four. These data show the effectiveness of the FSMC proposed in this paper.

Bio-Inspired New Hydraulic Actuator Imitating the Human Muscles for Mobile Robots.

Limited load capacity is the bottleneck for the practical application of mobile multi-joint legged robots. And improving the efficiency of the drive system is a key factor in improving the load capacity. To improve the efficiency of mobile robots, in this paper, a new kind of actuator that imitates the driving mechanism of human muscles is innovatively designed and validated through experiments. The proposed actuator consists of a single power source and multiple plunger pistons, and imitates the configuration of a human muscle, to improve the efficiency and load capacities. The design proposed here represents a new class of driving methods. The actuator selects the most appropriate combination of the effective areas of plunger pistons like the human muscles, to ensure that the maximal output force aligns with the load force. To validate that the new actuator can improve the efficiency of hydraulic systems of mobile robots, a robotic arm incorporating a prototype of the new actuator was designed. The proposed system was validated through a series of experiments. The experiments show that the bionic actuator can adjust the flow rate of the system input by adjusting the number and size of the motion units involved in the work, and with the change in load force, it changes the output force by recruiting different motion units, which indicates good controllability. The results reported herein reveal that the application of bionics to the design of robotic actuator can significantly improve the efficiency and overall performance of the robots, and this biomimetic approach can be applied to a variety of robots.

Flexural Properties of Multi-Tow Structures Constructed from Glass/Polypropylene Tape under Various Manufacturing Conditions

In this study, a multi-tow structure that can provide load-bearing functionality was fabricated through a proposed consolidation process proposed using polypropylene-impregnated continuous-glass-fiber composite tape (glass/PP tape). The flexural properties of the multi-tow structure were analyzed to evaluate the influence of the processing temperature, processing speed, number of glass/PP tapes, and glass fiber content of the glass/PP tapes. The proposed process for constructing the multi-tow structure can generate straight, curved, and looped three-dimensional structures by using a multi-joint robot and instantaneous consolidation of glass/PP tapes. As the number of glass/PP tapes increased, the resin-rich area increased and the void volume fraction in the multi-tow structure increased from 2 to 5 vol%, while the flexural strength decreased. However, when the number of glass/PP tapes and processing temperature were adjusted appropriately, the flexural strength of the multi-tow structure that can be constructed at speeds 30 times faster than those of conventional pultrusion process was relatively superior. The results of a finite element analysis, confirmed that the inclusion of the proposed multi-tow structure in a bumper beam was effective in reducing deformation and absorbing the impact energy due to external loads.

Coupling Effect Suppressed Compact Surgical Robot with 7-Axis Multi-Joint Using Wire-Driven Method

Currently, the most prevalent surgical treatment method is laparoscopic surgery. Robotic surgery has many advantages over laparoscopic surgery. Therefore, robotic surgery technology is currently constantly evolving. The advantages of robotic surgery are that it can minimize incision, bleeding, and sequelae. Other advantages of robotic surgery are that it can reduce hospitalization, recovery period, and side effects. The appeal of robotic surgery is that it requires fewer surgical personnel compared to laparoscopic surgery. This paper proposes an ultra-compact 7-axis vertical multi-joint robot that employs the wire-driven method for minimally invasive surgery. The proposed robot analyzes the degree of freedom and motion coupling for control. The robot joint is composed of a total of seven joints, and among them, the 7-axis joint operates the forceps. At this time, the forceps joint (#7 axis) can only operate open and close functions, while the link is bent and rotatable, regardless of position change. This phenomenon can be analyzed by Forward Kinematics. Also, when the DOF rotates, the passing wires become twisted, and the wire is generated through length change and coupling phenomenon. The maximum rotation angle of DOF is 90° and the rotating passing wire is wound by the rotation of the wire pulley. If the DOF is rotated to the full range of 120°, the second DOF will be rotated to 90°, and at this time, the coupling phenomenon caused by the first DOF rotation can be eliminated. The length change and the robot joint angle change related to the motor drive, based on the surgical robot control using the wire-driven method, are correlated, and the values for the position and direction of the end effector of the robot can be obtained through a forward kinematic analysis. The coupling problem occurring in the wire connecting the robot driving part can be solved through a kinematic analysis. Therefore, it was possible to test the position of the slave robot and the performance of the surgical forceps movement using the master system.

Traditional Catering Industry Carries Cooperative Robots to Achieve Industrial Upgrading

The world-renowned Chinese cuisine has been handed down from generation to generation in the traditional mode of handicraft, workshop and apprenticeship, which is distorted from generation to generation. The quality of dishes in small shops is difficult to guarantee, the works of masters are difficult to replicate, economies of scale are difficult to achieve, waste of resources can not be controlled, and the plight of industrialization has not been broken through. In recent years, with the development of science and technology, especially the growing maturity of cooperative robots, the traditional catering industry has ushered in an opportunity for innovation. Through the application research of multi-joint cooperative robot in Chinese cooking scene, this paper solves the technical difficulties of large-scale mechanization of Chinese cooking, opens up the last kilometer of Chinese food industrialization, realizes the upgrading of traditional catering industry, and also enables the inheritance and innovation of Chinese cooking.

Research on Robot Trajectory Planning Strategy for Water Polo Confrontation

In the multi-joint robot water polo competition, it often occurs that the robot fish glances off the ball when pushing it due to the water waves generated by the fish swimming and the influence of the opponent fish’s attack behavior on the target ball. In order to improve the success rate of the robot fish hitting the ball, this paper proposes a long-distance posture adjustment strategy and double-fish alternative attack strategy. The long-distance posture adjustment strategy is based on the detailed division of the relative positions of the fish, the ball and the goal. The probability of the fish, the ball and the goal being in a three-point line is improved by setting the distance through which the fish body reaches the preset hitting point and the posture adjustment strategy. Besides, the double-fish alternative attack strategy is proposed on the basis of this ball-pushing strategy. The cooperation between the two fishes is strengthened by developing another fish’s returning strategy during the opponent fish hitting the ball, thereby improving the attack efficiency. The experimental results show that the underwater robot fish can avoid the close touch-ball and can attack the ball into the goal more quickly and accurately.

Improvement in Accuracy of a Multi-Joint Robotic Ultrasonic Inspection System for the Integrity of Composite Structures

Composite materials have attracted significant attention with regard to the manufacturing of structures that require weight reduction, such as automobiles and aircraft, because they are more resistant to corrosion and fatigue than conventional metal materials. However, such materials exhibit a reliability degradation problem, i.e., their mechanical and physical properties deteriorate due to the occurrence of delamination and voids. Ultrasonic inspection methods have been widely applied for nondestructive detection of such defects in structures; however, the application of these approaches has been impeded due to high anisotropy and acoustic attenuation. In addition, the existing ultrasonic inspection methods require considerable time and cost for the inspection of large materials or structures. These problems were addressed in this study by developing an automatic ultrasonic inspection system; this was achieved by adopting a squirter-type water injection device, which uses a multi-joint robot and the through-transmission ultrasonic method. In addition, a software program to correct axis misalignment was developed and verified to solve the deterioration in defect detectability and accuracy that was caused by axis misalignment, which may occur during the use of the developed system. This development was accomplished after measuring the coordinates of the deformed mechanical part using a three-dimensional laser measuring instrument.

Design of Control System for Multi-joint Robot Based on STM32

The motion of Bionic Hexapod spider robot is relatively flexible. It has high comprehensive performance and research value whether it is the stability of motion, the load capacity of fuselage, or the difficulty of control. In this project, a Bionic Hexapod spider robot with STM32 chip as the core control is designed. Combined with the actuator control board design action, the STM32 chip built-in timer is used to generate multiple PWM signals to drive the steering gear motion, so that the robot can achieve different posture. At the same time, a wireless remote controller based on NRF24L01 wireless module is designed to expand the usability of the project. On the basis of the simulation, the actual operation principle of the robot is verified, which lays a good theoretical foundation for the continuous improvement of the robot in the future.

Attitude data-based deep hybrid learning architecture for intelligent fault diagnosis of multi-joint industrial robots

Monitoring the transmission status of multi-joint industrial robots is very important for the accuracy of the robot motion. The fault diagnosis information is an indispensable basis for the collaborative maintenance of the robots in industry 4.0. In this paper, an attitude data-based intelligent fault diagnosis approach is proposed for multi-joint industrial robots. Based on the analysis of the transmission mechanism, the attitude change of the last joint is employed to reflect the transmission fault of robot components. An economical data acquisition strategy is performed by only installing one attitude sensor on the last joint of the multi-joint robot. Considering the characteristics of attitude data, a hybrid sparse auto-encoder (SAE) and support vector machine (SVM) approach, namely SAE-SVM, is subsequently presented to construct an intelligent fault diagnosis model by learning from the attitude dataset with multiple fault information. Experimental results show that the proposed fault diagnosis approach has promising performance in identifying different faults related to the reducer of a 6-axial multi-joint industrial robot accurately and reliably.

A postprocessing and path optimization based on nonlinear error for multijoint industrial robot-based 3D printing

Multijoint industrial robots can be used for 3D printing to manufacture the complex freeform surfaces. The postprocessing is the basis of the precise printing. Due to the nonlinear motion of the rotational joint, nonlinear error is inevitable in multijoint industrial robots. In this article, the postprocessing and the path optimization based on the nonlinear errors are proposed to improve the accuracy of the multijoint industrial robots-based 3D printing. Firstly, the kinematics of the multijoint industrial robot for 3D printing is analyzed briefly based on product of exponential (POE) theory by considering the structure parameters. All possible groups of joint angles for one tool pose in the joint range are obtained in the inverse kinematics. Secondly, the nonlinear error evaluation based on the interpolation is derived according to the kinematics. The nonlinear error of one numerical control (NC) code or one tool pose is obtained. The principle of minimum nonlinear error of joint angle is proposed to select the appropriate solution of joint angle for the postprocessing. Thirdly, a path smoothing method by inserting new tool poses adaptively is proposed to reduce the nonlinear error of the whole printing path. The smooth level in the smoothing is proposed to avoid the endless insertion near the singular area. Finally, simulation and experiments are carried out to testify the effectiveness of the proposed postprocessing and path optimization method.

Robot posture generation method for laser melting deposition

PurposeThis paper aims to provide a posture generation method of robot deposition paths based on intersection topology, which is helpful to contribute to improving the flexibility and deposition capability of the deposition system.Design/methodology/approachVia the geometry information and normal vector information of the stereolithography (STL) model, the intersecting edge information is generated and the topological relationship of the model is established. Through the removal of redundant points for the STL model and the sort of robot path points, the position information of robot path points is obtained. According to the geometric relationship between the normal vector information of the STL model and the robot deposition path points, combining with the robot posture representation method of roll-pitch-yaw angles, the posture information of path points is achieved. Then, the generation from CAD model of parts to robot paths for laser melting is realized, and the experimental verification is carried out.FindingsFor simple parts, the laser melting process can be completed without the posture information of deposition paths. However, in the melting process of a turbine blade, there are some accumulated burls on the sidewall. The posture generation method of robot deposition paths based on the intersection topology can solve this problem. The light spot of deposition points irradiates on the surface of the forming part, and the forming process can proceed smoothly.Practical implicationsAs a motion platform in laser melting deposition (LMD), the application of the multi-joint robot can improve the flexibility and deposition capability of the deposition system, as well as promote the LMD application for individuation manufacturing, parts repair and green remanufacturing.Originality/valueThe posture is essential for robot deposition paths. This paper first proposes a posture generation method of deposition paths for LMD to improve the flexibility and deposition capability of LMD systems.