Robot Joint Research Articles

A Factor Graph Approach to Simultaneous Robot-World and Hand-Eye Calibration Based on Lie Group

The existing robot-world and hand-eye calibration algorithms always treated the robot pose as a deterministic value. Its uncertainty is not taken into account, which affects the calibration accuracy when the robot’s position accuracy is low. In this paper, we proposed a factor graph approach to simultaneous robot-world and hand-eye calibration, which considers the measurement error of the robot joint encoder. And then, the nonlinear optimization of reprojection error minimization based on a product of exponentials (POE)-based model is implemented to solve the calibration problem based on lie groups. Through simulation and experiment, we validated that the proposed algorithm can get more accurate calibration results compared with the state algorithm.

Methodology for model-based uncertainty quantification of the vibrational properties of machining robots

In order to increase the efficiency of modern, robot-based machining processes, a precise model of the robot’s vibrational properties is essential. In particular, a reliable estimation of the robot’s eigenfrequencies is crucial to estimate stable process parameters. However, the prediction of the eigenfrequencies is often imprecise, since the model relies on joint compliance parameters, whose identification process itself is prone to errors. The following paper addresses this issue by quantifying the uncertainty of the eigenfrequency prediction based on a novel, probabilistic compliance identification and a subsequent Monte Carlo uncertainty propagation . The uncertainty quantification is completed by a sensitivity analysis. • The prediction of the robot’s eigenfrequencies is often imprecise, since the model relies on joint compliance parameters, whose identification process itself is prone to errors. • A Bayesian inference approach allows a posterior distribution of the joint compliance parameters to be estimated by updating physical domain knowledge in the form of the prior with the observed system behavior. • The Bayesian identification of the robot joint compliance parameters allows quantifying the resulting uncertainty of the eigenfrequency prediction using the dynamic robot model and a Monte Carlo simulation approach. • A variance-based global sensitivity analysis is able to quantify the effect of the uncertain compliance parameters on the uncertainty of each estimated eigenfrequency of the robot.

Manufacturing and controlling 5-axis ball screw driven industrial robot moving through G codes

These days, in industrial robot applications, servo motors with reducer have been used to move robot manipulators. Due to the weight of the robot parts, it causes undesirable conditions such as backward movement, downward movement and vibration caused by the moments of inertia at the time of movement. In this study, step motor ball screw driven actuators, which use push-pull force instead of servo motor with reducers, were utilized to provide rotational movement in robot arms. The ball screw system reduces the effect of moments of inertia caused by the movements of the robot joints, and restricts the free movements of the robot joints. It also provides an advantage by reducing costs since it uses smaller motors. In articulated robots, the complexity of kinematic equations and the use of high-order polynomials for trajectory planning cause difficulties in controlling. In this study, the information of the points, where the robot went during the manual movement, was obtained by using the macros prepared in program interface without using kinematic and trajectory planning equations. The position lines taken at these points were printed in a text file by adding the code G01 and f feed-rate. The robot was made to move by running this file in the program interface used for control. This method allows the operator to use the robot without advanced kinematics knowledge.

Passive Impedance Control of Robots With Viscoelastic Joints Via Inner-Loop Torque Control

This article presents passive impedance control of flexible joint robots (FJRs) via inner-loop torque control of elastic joints. However, according to our theoretical analysis, the torque control methods of series elastic actuators (SEAs) are often limited by the fact that the acceleration signals are amplified by the control gains. Since the acceleration signals are often affected by differentiation noise, the analysis may become invalid in practice. To alleviate this limitation, we propose the use of the so-called series viscoelastic actuator (SvEA), which significantly reduces the acceleration amplification. Consequently, in contrast to the SEA case, the theoretical analysis of an SvEA-based FJR is valid in real implementations. We would like to highlight the fact that the theoretical analysis (more specifically, passivity analysis) is performed for nonlinear robot dynamics without linearization. As a result, the passive impedance controller can be realized more robustly with enhanced inner-loop torque control.

Optimal trajectory generation method to find a smooth robot joint trajectory based on multiquadric radial basis functions

Optimal trajectory generation method to find a smooth robot joint trajectory based on multiquadric radial basis functions

A Variable Parameter Method Based on Linear Extended State Observer for Position Tracking

This paper presents a control strategy with a linear extended state observer (LESO) and Kalman filter to achieve a high performance of the motion control system. The moment of inertia of the system, which is variable with the robotic joint motion, is estimated in the established model. A LESO with variable gain is designed, which could estimate the states and the total disturbance of the plant without a precision mathematical model. The disturbance caused by variable load and unknown dynamics can be compensated based on the LESO, while the moment of inertia is variable. In order to restrain the process noise and measure the noise of the system, the Kalman filter was applied. Tracking differentiator was utilized to avoid the overshoot of the system for the step signal. The designed control strategy with the LESO and the Kalman filter could improve the tracking performance for the servo system with parametric uncertainties, unknown dynamics, and disturbances. The effectiveness of the proposed method is implemented and validated in the experiment of the robotic joint, for which desired servo tracking performance is achieved with the conditions of load variation and sudden disturbance.

A new low-energy nonlinear variable stiffness actuator for the knee joint

With the increase of safety requirements for human-robot interaction, variable stiffness actuators are increasingly used in joints of medical rehabilitation robots, legged mobile robots and exoskeleton-assisted robots, so the research of the variable stiffness actuator becomes more and more important. In this paper, firstly, according to the human knee joint, a low-energy nonlinear variable stiffness actuator for knee joint is proposed, it conforms to characteristics of biological joints: the actuator can be flexible when it is subjected to the small load, and the actuator can be stabilized when it is subjected to the heavy load. The realization principle of this actuator, which is combining the eccentric cam with the leaf spring, is introduced in detail, and its relatively large range of variable stiffness is accurately deduced and analyzed. Secondly, the energy cost of this actuator is reduced as much as possible by some structural designs. Finally, by experiments, the correctness and accuracy of the resistance moment and expected stiffness of the proposed nonlinear variable stiffness actuator are verified, the high bandwidth and good stability of this actuator are also verified, which meets the design principles and requirements of the actuator, and it is verified that actuator’s low energy cost.

Kinematics analysis and gait planning for a hemiplegic exoskeleton robot

Background: As the world's aging population increases, the number of hemiplegic patients is increasing year by year. At present, in many countries with low medical level, there are not enough rehabilitation specialists. Due to the different condition of patients, the current rehabilitation training system cannot be applied to all patients. so that patients with hemiplegia cannot get effective rehabilitation training. Methods: Through a motion capture experiment, the mechanical design of the hip joint, knee joint and ankle joint was rationally optimized based on the movement data. Through the kinematic analysis of each joint of the hemiplegic exoskeleton robot, the kinematic relationship of each joint mechanism was obtained, and the kinematics analysis of the exoskeleton robot was performed using the Denavit-Hartenberg (D-H) method. The kinematics simulation of the robot was carried out in automatic dynamic analysis of mechanical systems (ADAMS), and the theoretical calculation results were compared with the simulation results to verify the correctness of the kinematics relationship. According to the exoskeleton kinematics model, a mirror teaching method of gait planning was proposed, allowing the affected leg to imitate the movement of the healthy leg with the help of an exoskeleton robot. Conclusions: A new hemiplegic exoskeleton robot designed by Shenzhen Institute of Advanced Technology (SIAT-H) is proposed, which is lightweight, modular and anthropomorphic. The kinematics of the robot have been analyzed, and a mirror training gait is proposed to enable the patient to form a natural walking posture. Finally, the wearable walking experiment further proves the feasibility of the structure and gait planning of the hemiplegic exoskeleton robot.

Parametric joint compliance analysis of a 3-UPU parallel robot

Sufficiently low compliance is required for robot end-effectors to perform various tasks with high static and dynamic accuracy. The joint compliance and link compliance of robots are the two major factors for the determination of overall end-effector compliance. Unlike serial robots that can allow larger joint sizes to improve the joint compliance, the joints of parallel robots are usually closely located and hence the joint size cannot be easily increased. Compared with the link compliance, the joint compliance of a parallel robot contributes more to the end-effector compliance, but its importance is often overlooked. To reduce the computational intensity of robot compliance design, analytical joint compliance models are proposed for the class of 3-UPU parallel robots. These joint compliance models can be used to quickly evaluate the compliance contribution of each revolute joint at various parallel robot configurations. Numerical and experimental verifications are provided to demonstrate these models. We expect that the parametric analysis of 3-UPU parallel robot compliance can be facilitated by using the proposed joint compliance models.

A novel model-based robust control design for collaborative robot joint module

In order to reduce the impact of load and system parameter changes on the dynamic performance of collaborative robot joint module, a novel robust control algorithm is proposed in this paper to solve the problem of dynamic control of collaborative robot joint module trajectory tracking. The controller is composed of two parts: one is a nominal control term designed based on the dynamical model, aiming to stabilize the nominal robot system; the other is a robust control term based on the Lyapunov method, aiming to eliminate the influence of uncertainty on tracking performance, where the uncertainties include nonlinear friction, parameter uncertainty, and external disturbances. The Lyapunov minimax method is adopted to prove that the system is uniformly bounded and uniformly ultimately bounded. We performed numerical simulation and experimental validation based on an actual collaborative robot joint module experimental platform and the rapid controller prototype cSPACE. The numerical simulation and experimental results show that the controller has excellent control performance for the collaborative robot joint module and provides more accurate trajectory tracking under the influence of uncertainties.

Model-based robust control design and experimental validation of SCARA robot system with uncertainty

In this paper, we design a novel robust control method to reduce the trajectory tracking errors of the SCARA robot with uncertainties including parameters such as uncertainty of the mechanical system and external disturbance, which are time-varying and nonlinear. Then, we propose a deterministic form of the model-based robust control algorithm to deal with the uncertainties. The proposed control algorithm is composed of two parts according to the assumed upper limit of the system uncertainties: one is the traditional proportional-derivative control, and the other is the robust control based on the Lyapunov method, which has the characteristics of model-based and error-based. The stability of the proposed control algorithm is proved by the Lyapunov method theoretically, which shows the system can maintain uniformly bounded and uniformly ultimately bounded. The experimental platform includes the rapid controller prototyping cSPACE, which is designed to reduce programming time and to improve the efficiency of the practical operation. Moreover, we adopt different friction models to investigate the effect of friction on robot performance in robot joints. Finally, numerical simulation and experimental results indicate that the control algorithm proposed in this paper has desired control performance on the SCARA robot.

Robotic assisted artificial hip and knee arthroplasty is an inevitable trend in the future

Artificial joint arthroplasty, such as total hip and total knee arthroplasty, is one of the most successful procedures in orthopedics. The quality of life of these patients can be improved significantly through relieving pain, correcting the deformity and improving joint function. Although hip and knee arthroplasty currently are routine surgeries for patients with late stage joint diseases, post-operative complications like leg length discrepancy, dislocation or instability, limp and uncertain reason pain are still common. The position of the implants plays important roles in all these complications. Robotic assisted joint arthroplasty can not only provide 3D pre-operative visual planning, but also can assist to fulfill the pre-operation plan perfectly. But the current joint arthroplasty robots cannot carry out automatic personalized pre-operation planning, and also have the shortcomings of low efficiency and high cost etc. However, based on their current performance and with the help of artificial intelligence and better algorithm, we believe that joint arthroplasty will be more and more precisive, intelligent and minimally invasive, which is an inevitable trend in the development of joint surgery.

ExGenNet: Learning to Generate Robotic Facial Expression Using Facial Expression Recognition.

The ability of a robot to generate appropriate facial expressions is a key aspect of perceived sociability in human-robot interaction. Yet many existing approaches rely on the use of a set of fixed, preprogrammed joint configurations for expression generation. Automating this process provides potential advantages to scale better to different robot types and various expressions. To this end, we introduce ExGenNet, a novel deep generative approach for facial expressions on humanoid robots. ExGenNets connect a generator network to reconstruct simplified facial images from robot joint configurations with a classifier network for state-of-the-art facial expression recognition. The robots’ joint configurations are optimized for various expressions by backpropagating the loss between the predicted expression and intended expression through the classification network and the generator network. To improve the transfer between human training images and images of different robots, we propose to use extracted features in the classifier as well as in the generator network. Unlike most studies on facial expression generation, ExGenNets can produce multiple configurations for each facial expression and be transferred between robots. Experimental evaluations on two robots with highly human-like faces, Alfie (Furhat Robot) and the android robot Elenoide, show that ExGenNet can successfully generate sets of joint configurations for predefined facial expressions on both robots. This ability of ExGenNet to generate realistic facial expressions was further validated in a pilot study where the majority of human subjects could accurately recognize most of the generated facial expressions on both the robots.

Observer‐based adaptive control of cooperative multiple manipulators using the Mastroianni operators as uncertainty approximator

AbstractThis article addresses the multi‐objective problem of pose and force control in a cooperative system comprised of multiple n‐degree‐of‐freedom (n‐DOF) robotic arms that move a payload. The proposed controller should be capable of maintaining the position and orientation of the payload in the desired path. In addition, the force exerted by robot end‐effectors on the object must remain limited. The system has unmodeled dynamics, and measuring the robot joint velocities is impossible. In other words, joint positions are the only measured states. Therefore, a Mastroianni operator‐based observer is first designed to estimate the uncertainty and velocities based on its universal approximation property. Then, using these estimations, a feedback controller is proposed to establish a robust and precise tracking performance. The stability of this system is confirmed based on Lyapunov's stability theorem. This article is the first study on utilizing the adaptive form of Mastroianni operators in robust adaptive controller design. Moreover, the introduced structure is regressor‐free and does not depend on velocity measurements. Finally, the proposed adaptive observer‐controller is applied on two 3‐DOF cooperative robotic arms carrying a payload, and the results are precisely analyzed. The results of the proposed approach are also compared with a state‐of‐art powerful approximation method.

Design of Asymmetric Parallel Manipulator for Axial-Bending Dynamic Stiffness Analysis

This paper presents an asymmetric 5-bar parallel manipulator capable of characterizing the dynamic stiffness properties of materials used in robotic joints in 2 degrees of freedom, axial and bending, simultaneously. The end effector is actuated by two stepper motors with linear rails. Two force sensors were added to estimate axial force and moment. Experiments were performed in axial compression, bending, and a mixed axial-bending motion. A spring-mass-spring system was constructed to evaluate the fabricated apparatus for frequency analysis up to 20Hz. The frequency analysis result was accurate when compared to the theoretical response of the system. Axial stiffness estimation had an error of 1.5%, bending stiffness had an error of 3.4%, and mixed-mode had a total error of 1.8%. Future experiments will showcase the versatility of the apparatus and test nonlinear samples.

Dizajn i razvoj sistema robotskih ruku za klasifikaciju i sortiranje primenom mašinskog vida

The main focus of this paper is to design and develop a system of two robot arms for classifying and sorting objects based on shape and size using machine vision. The system uses a low-cost and high-performance hierarchical control system including one master and two slaves. Each slave is a robot controller based on a microcontroller that receives commands from the master to control the robot arm independently. The master is an embedded computer used for image processing, kinematic calculations, and communication. A simple and efficient image processing algorithm is proposed that can be implemented in real-time, helping to shorten the time of the sorting process. The proposed method uses a series of algorithms including contour finding, border extraction, centroid algorithm, and shape threshold to recognize objects and eliminate noise. The 3D coordinates of objects are estimated just by solving a linear equation system. Movements of the robot's joints are planned to follow a trapezoidal profile with the acceleration/deceleration phase, thus helping the robots move smoothly and reduce vibration. Experimental evaluation reveals the effectiveness and accuracy of the robotic vision system in the sorting process. The system can be used in the industrial process to reduce the required time to achieve the task of the production line, leading to improve the performance of the production line.

Slantlet transform used for faults diagnosis in robot arm

<p class="JESTECAbstract">The <span>robot arm systems are the most target systems in the fields of faults detection and diagnosis which are electrical and the mechanical systems in many fields. Fault detection and diagnosis study is presented for two robot arms. The disturbance due to the faults at robot's joints causes oscillations at the tip of the robot arm. The acceleration in multi-direction is analysed to extract the features of the faults. Simulations for planar and space robots are presented. Two types of feature (faults) detection methods are used in this paper. The first one is the discrete wavelet transform, which is applied in many research's works before. The second type, is the Slantlet transform, which represents an improved model of the discrete wavelet transform. The multi-layer perceptron artificial neural network is used for the purpose of faults allocation and classification. According to the obtained results, the Slantlet transform with the multi-layer perceptron artificial neural network appear to possess best performance (4.7088e-05), lower consuming time <br /> (71.017308 sec) and higher accuracy (100%) than the results obtained when applying discrete wavelet transform and artificial neural network for the same </span>purpose.</p>

Compliance Control System Design for Sub-Crawler Rotary Joints of Ground-Adaptive Crawler Robot

Compliance Control System Design for Sub-Crawler Rotary Joints of Ground-Adaptive Crawler Robot

Analysis Randon Causes Repeatability Errors Inducted by Friction at Joints in Industrial Robots

The present study was carried out to investigate and analyze the positionning repeatability introduced by friction variations based on stochastic ellipsoids. A mixed friction model has been developed with improved properties compared to existing standard models. The contact is presented as a multitude of micro contacts whose nature can be of two types: lubricated and solid. This model is experimentally tested on a reciprocating tribometer under extreme friction conditions, with sliding speed varying from 0.1 to 3 m/s and load modified from 40N to 150N to discuss the effect of speed, the effect of nominal contact pressure and the effect of sliding distance on friction parameters. The results showed how this model can be represented as a sum of functions of the relevant states, which are linear and nonlinear in the friction parameters. Thus, these results were used to evaluate the covariance matrix in order to locate the different ranges of errors which have an impact on the repeatability of position.

A Robotic Torso Joint With Adjustable Linear Spring Mechanism for Natural Dynamic Motions in a Differential-Elastic Arrangement

To be operated in unknown or complex environments, modern robots have to fulfill various challenging criteria. Among them, one finds requirements such as a high level of robustness to withstand impacts and the capabilities to physically interact in a safe manner. One way to achieve that is to integrate variable-stiffness actuators into the systems, enabling compliant behavior through the elastic components and providing the additional adaptability of the impedance. Here, we introduce a novel adjustable linear stiffness joint mounted in a differential-elastic arrangement. The mechanism is integrated into the anthropomorphic upper body of the DLR David robot and responsible for the spinal rotation. Consequently, the actuator is crucial for the overall workspace of the robot and the realization of energy-efficient natural motions such as in dynamic running. The proposed hardware setup is experimentally validated in terms of the linearity in the spring characteristics, intrinsic damping, the excitation of resonance frequencies, and the ability to alter these resonance frequencies through stiffness adaptation during dynamic motions.