End-effector Research Articles

Disturbance observer‐based control for cable‐driven parallel robots with external disturbance using deep reinforcement learning

AbstractIn cable‐driven parallel robots (CDPRs) practical applications, external disturbances inevitably influence the actuator performance, leading to low positioning accuracy of end‐effector (EE), and even system crashes. This paper addresses a disturbance observer‐based control scheme using deep reinforcement learning (RL) to suppress the effect of external disturbances. A controller via the non‐singular terminal sliding mode (NTSM) is proposed to enhance the system robustness. The estimation of the disturbance is investigated, and the deep RL is employed to enhance the model‐based disturbance observer, namely, the RLDO, and a corresponding controller via NTSM (RLDO‐NTSMC) is proposed. Simulations and experimental results validate that the RLDO effectively improves the estimation accuracy, and the RLDO‐NTSMC significantly increases the control accuracy of CDPRs. The root mean square errors of the EE's positioning errors controlled by the RLDO‐NTSMC decreased by over 93% compared with the classical augmented proportional–derivative (APD) controller.

Numerical study of transient supercooling performance and thermal stress analysis of segmented annular thermoelectric cooler

A multiphysics-coupled numerical simulation of a segmental annular thermoelectric cooler (SATEC) was performed using a three-dimensional finite element method. A coupling model of the temperature, stress, and electric fields was established based on the three-dimensional transient states. Moreover, the effects of different pulse width (τ), pulse current amplitude (Pa), pulse current shape parameter (m), heat transfer coefficient (h), angle (θ), and length (H) of the thermoelectric leg on the SATEC transient properties and von Mises stress were studied. The results show that τ and Pa are the key influencing factors of SATEC. The larger the h, the more optimized the heat transfer effect of the SATEC hot end. However, when h increased to a certain value, the changes in the transient performance were insignificant. The optimal pulse can be achieved when the input pulse current Iop = 6.47 A and pulse width τ = 20 s. When the length of the thermoelectric leg H4 was 3 mm and the thermoelectric leg angle θ2 was 7°, the performance of SATEC was optimal, with Tc,min being 249.57 K, Tc,max being 279.50 K, thold being 5.5 s, and the maximum von Mises stress being 37.48 MPa. The results show that different supercooling indices and von Mises stresses could be obtained for different pulse current shapes. Geometric optimization of SATEC can improve the cooling performance and reduce the von Mises stress, thereby providing a theoretical reference for practical engineering applications and thermoelectric cooling research.

Numerical study of effective parameters on true triaxial test results in rigid type apparatus

Operational parameters in true triaxial loading devices (TTA), such as the loading rod dimensions, friction between the loading platens and sample faces, loading gap, and one-side loading may affect the test results. Knowledge of the effect of each parameter is very important to correctly interpret rock behavior and to optimize these devices. Employing the Flac3D finite difference software, a rigid type true triaxial systemdesigned and builtat Amirkabir University of Iran (AUT-TTA) was simulated andinvestigated in this study. The results indicate that increasing the ratio of the rod cross-section to the loading platen area leads to an increase in the sample confinement, so, more uniform stress distribution occurs in the rock sample. The loading gap reduces strength of the rock specimen and leads to concentration of tensile stresses at the sample edges. The end effect leads to an increase in the stress level and a pseudo-hardening behavior in the samples. Also, the end effect is intensified under one-side loading condition compared to two-side loading. Comparison between results of AUT-TTA numerical simulation and analytical analysis (ideal conditions without considering operational parameters) indicates that the slope of the stress–strain diagram has low sensitivity to operational parameters. The most important operational factor affecting the stress level and dilatation stress is the end effect and other operational parameters have little effect. All parameters lead to an increase in the dilation strain. The clear edge and one-sided loading under low intermediate principal stresses and the end effect under high intermediate principal stresses have the greatest effect on the dilation strain.

Utilization of Manipulator Redundancy for Torque Reduction During Force Interaction

Abstract The integration of robots into environments shared by humans has been enhanced through the use of redundant robots capable of executing primary tasks and secondary objectives such as obstacle avoidance and null-space impedance control. A critical secondary objective involves optimizing manipulator configurations to reduce torque and prevent torque saturation, similar to how athletes distribute loads to minimize the risk of injury. This paper suggests employing robotic redundancy to evenly distribute joint loads, thereby improving performance and avoiding torque saturation. Prior studies primarily focused on either endpoint stiffness control or kinetic energy minimization, each having its drawbacks. This paper introduces a novel objective function that responds to all external disturbances at the end-effector, aiming to lower joint torques via redundancy for precise trajectory tracking amidst disturbances. This method, which provides an inverse kinematics solution adaptable to various controllers, demonstrated a 29.85% reduction in peak torque and a 14.69% decrease in cumulative torques in the KUKA LBR iiwa 14 R820 robot.

A novel vision-based multi-functional sensor for normality and position measurements in precise robotic manufacturing

Cobots play an essential role in the fourth industrial revolution and the automation of complex manufacturing processes. However, cobots still face challenges in achieving high precision, which obstructs their usage in precise applications such as the aerospace industry. Nonetheless, advances in perception systems unlock new cobot manufacturing capabilities. This paper presents a novel multi-functional sensor that combines visual and tactile feedback using a single optical sensor, featuring a moving gate mechanism. This work also marks the first integration of Vision-Based Tactile Sensing (VBTS) into a robotic machining end-effector. The sensor provides vision-based tactile perception capabilities for precise normality control and exteroceptive perception for robot localization and positioning. Its performance is experimentally demonstrated in a precise robotic deburring application, where the sensor achieves the high-precision requirements of the aerospace industry with a mean normality error of 0.13° and a mean positioning error of 0.2 mm. These results open a new paradigm for using vision-based sensing for precise robotic manufacturing, which surpasses conventional approaches in terms of precision, weight, size, and cost-effectiveness.

Optimized Design of Robotic Arm for Tomato Branch Pruning in Greenhouses

Aiming at the robotic pruning of tomatoes in greenhouses, a new PRRPR configuration robotic arm consisting of two prismatic (P) joints and three revolute (R) joints was designed to locate the end effector to handle randomly growing branches with an appropriate posture. In view of the various spatial posture of the branches, drawing on the skill of manual pruning operation, we propose a description method of the optimal operation posture of the pruning end effector, proposing a method of solving the inverse kinematics of the pruning arm based on the multi-objective optimization algorithm. According to the spatial distribution characteristics of the tomato branches along the main stem, the robotic arm structure is compact and the reachable space is maximized as the objective function, and a method of optimizing the key geometric parameters of the robotic arm is proposed. The optimal maximum length of the arm’s horizontal slide joint was determined to be 953.149 mm and the extension maximum length of its telescopic joint was 632.320 mm. The verification test of the optimal structural parameter showed that the optimized robotic arm could reach more than 89.94% of the branches in the pruning target area with a posture that meets the pruning requirements. This study is supposed to provide technical support for the development of a tomato pruning robot.

DDPG-based reinforcement learning for controlling a spatial three-section continuum robot

This paper proposes an approach to controlling a spatial three-section continuum robot using reinforcement learning (RL). Rather than relying on traditional methods that use bending and orientation angles, this study utilizes the curvature of each section to achieve the desired position. The training process involves identifying a 3D workspace for the robot and utilizing a deep neural network to optimize its control policies. The results demonstrate that the robot’s end effector can follow a given trajectory with a maximum error of 1 [1/mm] based on the generated curvature for each section. The Deep Deterministic Policy Gradients (DDPG) algorithm is employed to optimize the robot’s control policies. Additionally, the developed DDPG algorithm is compared to the Deep Q-Network (DQN) from a precision standpoint, particularly during the tracking of a circular trajectory. This comparison highlights the superior accuracy of DDPG in managing the intricate movements required for continuum robotics, making it a promising tool for applications where precision is crucial, such as in medical and surgical robotics.

Rolling bearing fault diagnosis based on improved whale-optimization- algorithm–variational-mode-decomposition method

Rolling bearings are a key component of rotating machinery and their health directly affects the safe operation of mechanical equipment. Therefore, fault diagnose for rolling bearings is very important. The fault diagnosis process of rolling bearings includes three stages: signal decomposition, feature extraction, and pattern recognition. Variational mode decomposition (VMD) can suppress end effects, but improper parameter settings will cause information losses or excessive decomposition. In this work, an improved whale optimization algorithm (IWOA) is applied to parameter settings of VMD. Correspondingly, an IWOA-VMD signal decomposition method is proposed. The decomposed signal is combined with a Laplace score method and classifier to remove the redundancy and noise in the feature set and obtain a low-dimensional sensitive feature subset. Then, aiming at the problem of the parameter settings of a least squares support vector machine (LSSVM) affecting the recognition performance and accuracy, a salp swarm algorithm (SSA) is used to globally optimize the penalty parameter and kernel width in the LSSVM to establish an SSA-LSSVM fault recognition model. This model is applied to the fault diagnosis of rolling bearings. In particular, rolling bearing fault samples at Case Western Reserve University are used to verify the method. The results indicate that the proposed method is effective and improves the speed and accuracy of fault diagnosis.

Optimizing pick-place operations: Leveraging k-means for visual object localization and decision-making in collaborative robots

This article presents an approach to object localization algorithms for pick-place operations in collaborative robots by utilizing conventional color segmentation in computer vision and k-means clustering. Adding the k-means clustering algorithm complements the color segmentation by distinguishing and grouping the sections of similar pixels; hence, object localization is more accurate. The order of pick-place operations of each cluster acquired from the proposed algorithm is prioritized based on norm. Integrating the proposed framework provides a well-structured depiction of the localized objects, which is fundamental for successful pick-place operations. The TCP/IP communication framework via socket communication is established to facilitate data transmission between the robot and the host computer. The objective is to ensure that the robot's end effector performs as directed by the host computer by obtaining information on the pick-and-place operation, including the localized coordinates, dimensions, the order of operations, and the pose of the objects of interest to the robot. In this experiment, a cobot arm is employed to autonomously pick and place objects with different shapes and colors in a workspace filled with diverse objects, requiring the robot to choose the closest objects to operate based on the data from the host computer. Our results demonstrate the effectiveness of this integration, showcasing the enhanced adaptability and efficiency of pick-place operations in collaborative robots. This study indicates 98% accuracy in pick-and-place operations with an average latency of 0.52 ± 0.1 s, indicating an improvement compared to the traditional algorithm without k-means clustering, which achieves an accuracy of 88%. Additional studies reveal that when incorporating pose estimation into the pick-place operations, the proposed algorithm's accuracy is 94%. The demonstration highlights the potential of leveraging machine learning algorithms and computer vision from the camera to perform flexible pick-place operations via socket communication.

Actuators for Improving Robotic Arm Safety While Maintaining Performance: A Comparison Study

Since robotic arms operating close to people are becoming increasingly common, there is a need to better understand how they can be made safe when unintended contact occurs, while still providing the required performance. Several actuators and methods for improving robot safety are studied and compared in this paper. A robotic arm moving its end effector horizontally and colliding with a person’s head is simulated. The use of a conventional electric actuator (CEA), series elastic actuator (SEA), pneumatic actuator (PA) and hybrid pneumatic electric actuator (HPEA) with model-based controllers are studied. The addition of a compliant covering to the arm and the use of collision detection and reaction strategies are also studied. The simulations include sensor noise and modeling error to improve their realism. A systematic method for tuning the controllers fairly is proposed. The motion control performance and safety of the robot are quantified using root mean square error (RMSE) between the desired and actual joint angle trajectories and maximum impact force (MIF), respectively. The results show that the RMSE values are similar when the CEA, SEA, and HPEA drive the robot’s first joint. Regarding safety, using the PA or HPEA with a compliant covering can reduce the MIF below the safety limit established by the International Organization for Standardization (ISO). To satisfy this ISO safety limit with the CEA and SEA, a collision detection and reaction strategy must be used in addition to the compliant covering. The influences of the compliant covering’s stiffness and the detection delay are also studied.

Utilizing Inverse Kinematics for Precise Guidance in Planning 6-DoF Robot End-Effector Movements

The solution of the kinematic inverse determines a substantial part of the robotic arm's control accuracy. Researchers frequently employ standard problem-solving techniques such as numerical, algebraic, iterative, and geometric methods. Although geometric like trigonometrical method has been widely studied, and their application is strongly dependent on the shape and dimensions of the robot. The complexity of the steps makes this approach difficult for researchers. In order to give a clearance and easiness, the step-by-step features of inverse kinematics are described in this research. The study begins with forward kinematics and refers to the DH-parameter in Homogeneous Matrix Transformations calculation. The existence of specific elements applied to mathematical derivation constituted the basis of forward kinematic discussions. And based on geometrical analysis, the inverse kinematic is then derived. Furthermore, simulations are performed to demonstrate the actual implementation of IK and the solution is then used to initiate the path planning process.

Optimization of acceleration and force ripple of planar motor based a chamfered magnet array considering coil end effect

According to the increasing throughput and precision requirements of the wafer stage, this paper proposes a new 2-D magnet array to improve the acceleration and force precision of the planar motor. Firstly, an analytical model of the magnet array with chamfered magnets is established based on the harmonic model, in which the influences of the installation height and the magnetization are included. Then, a modified discrete element model of the runway-type coil is proposed to achieve accurate and efficient force calculation because over half of the force ripple is generated by the coil end, which is neglected in the simplified model. Finally, the influence of chamfered magnet array on the field and force is analyzed. The genetic algorithm is used to optimize the planar motor, which results in a 64% reduction in vertical force tipple and a 1.24 times increase in horizontal acceleration.

Investigation of parasitic motion in 3-RRS parallel manipulator

This paper investigates the Parasitic Motion (PaMo) in a 3-Degree of Freedom (DoF) 3-RRS Spatial Parallel Manipulator (SPM) for its different link proportions. The position kinematic analysis of the manipulator is addressed initially. The PaMo is investigated and quantified as the percentage of Reachable Workspace (RW) for each link proportion at the tip of an End-Effector (EE), which is attached at the centroid of the moving platform. The PaMo which happens in the constrained DoF is an unwanted motion, and this entire process allows to know the total occupancy of PaMo in comparison to RW for each link proportion. The results are depicted with the aid of 3D plots of the reachable work-volume and the volume of PaMo for each link proportion. In order to evaluate the performance measure, a performance index called as the parasitic motion index ( PaMoI) is proposed. The PaMoI variation pattern is also discussed based on the obtained results. The conclusions are drawn at the end based on this investigation that also identify the provisions to minimize the PaMo.

Realization and Control of Robotic Injection Prototype With Instantaneous Remote Center of Motion Mechanism.

Although there have been studies conducted on the instantaneous remote center of motion (RCM) mechanism, the general closed-loop control method has not been studied. Thus, this article fills that gap and employs the advantages of this mechanism to develop a novel injection system. The injection prototype involves the instantaneous RCM mechanism, insertion unit and injection unit. The RCM system is investigated in the presence of time-varying axial stiffness of the screw drive and underactuated case. For safe interaction, compliance control is designed in the insertion system. The stability of all separate systems is investigated with the bounded parameter variation rate. The injection prototype and a robot end-effector were then combined to perform injection. Our RCM prototype can achieve a large workspace, and its control effectiveness was verified by multiple frameworks and comparison with previous studies. Compliance-controlled insertion can achieve accurate depth regulation and zero-impedance control for manually operating the needle. With the help of three-dimensional reconstruction and hand/eye calibration, the manipulator can guide the injection prototype to a proper pose for injection of a face model. The injection prototype was successfully designed. The effectiveness of the whole control system was verified by simulations and experiments. The particular robotic injection task can be performed by the prototype. This article provides alternative schemes for developing an instantaneous RCM system, screw drive-based surgical tool, and robotic insertion with small needles.

Robust Grasping of a Variable Stiffness Soft Gripper in High-Speed Motion Based on Reinforcement Learning.

Industrial robots are widely deployed to perform pick-and-place tasks at high speeds to minimize manufacturing time and boost productivity. When dealing with delicate or fragile goods, soft robotic grippers are better end effectors than rigid grippers due to their softness and safe interaction. However, high-speed motion causes the soft robotic gripper to vibrate, leading to damage of the objects or failed grasping. Soft grippers with variable stiffness are considered to be effective in suppressing vibrations by adding damping devices, but it is quite challenging to compromise between stiffness and compliance. In this article, a controller based on deep reinforcement learning is proposed to control the stiffness of the soft robotic gripper, which can accurately suppress the vibration with only a minor influence on its compliance and softness. The proposed controller is a real-time vibration control strategy, which estimates the output of the controller based on the current operating environment. To demonstrate the effectiveness of the proposed controller, experiments were done with a UR5 robotic arm. For different situations, experimental results show that the proposed controller responds quickly and reduces the amplitude of the oscillation substantially.

Large eddy simulation of end effects on a cylinder rotor

Due to the limited length of cylinders, their use in practical engineering inevitably involves end effects, which results in three-dimensional flows at the ends of cylinders. These flow fields are the main factor influencing the aerodynamic and flow field characteristics of cylinders. Regarding a finite-length cylinder rotor, a specific pattern of tip vortices will form under the action of rotation, resulting in notable differences in the aerodynamic characteristics between an ideal two-dimensional cylinder and a finite-length cylindrical rotor. In the present study, the large eddy simulation method is used to systematically investigate cylinder rotors with various aspect ratios. By analyzing the sectional aerodynamic and flow field characteristics, the variation laws of the aerodynamic force, wind pressure, and flow field characteristics of cylinder rotors under the influence of end effects were summarized. The results show that the influence range and intensity of the tip vortices on the rotor flow field and sectional aerodynamic characteristics are dominated by the dimensionless rotating speed, which in turn affects the range of the end effects. The development trend of the tip vortices is analyzed and discussed from multiple aspects, including sectional aerodynamics, the pressure coefficient, and the flow correlation, and an attempt is made to explain changes in the phenomenon.

Design and Analysis of a Breast Biopsy Robot Based on TRIZ Theory

Background: In recent years, more and more medical robots have formally stepped into clinical applications and are gradually being accepted by patients. Magnetic resonance image (MRI)-guided breast intervention robot is the most advanced technology for breast cancer treatment. Still, the very limited working space within the MRI scanner restricts the development of breast intervention robots. Objective: In this paper, a compact breast biopsy robot in MRI environment is proposed based on TRIZ theory. Methods: The structure of the robot is optimized by using the curvilinear principle and the asymmetry principle of TRIZ theory to obtain a modified cartesian coordinates robot for breast biopsy. The coordinate systems of the robot are established using D-H method. Next, 3D visualization simulation of the robot is performed by SimMechanics of MATLAB, and then kinematic simulation and workspace simulation analysis are carried out. Results: The simulation results show that motion space of the end effector of the robot meets the requirements of breast intervention surgery, and the robot structure is simple and effective. Conclusion: In this paper, a compact breast biopsy robot in MRI environment is proposed. Through the Simulink module of MATLAB to analyze its workspace, it is obtained that its working range is 250mm × 300mm × 200mm, which can cover any position in breast tissue. At the same time, the simulation results of the workspace also show that the structure optimization of the breast biopsy robot based on TRIZ theory is reasonable.

An Integrated Architecture for Robotic Assembly and Inspection of a Composite Fuselage Panel with an Industry 5.0 Perspective

Aeronautical robotic applications use quite large, heavy robots with huge end effectors that are frequently multifunctional. An assembly jig to hold a fuselage panel and two medium-sized six-axis robots fixed on linear axes, referred to as the internal and the external robot with respect to the curvature of the panel, make up the Lean robotized AssemBly and cOntrol of composite aeRostructures (LABOR) work cell. A distributed software architecture is proposed in which individual modules are developed to execute specific subprocesses, each implementing innovative algorithms that solve the main drawbacks of state-of-the-art solutions. Real-time referencing adopts a point-cloud-based strategy to reconstruct and process the part before drilling, avoiding hole positioning errors. Accurate concentric countersink diameters are made possible through the automatic adjustment of the drilling tool with respect to the skin panel, which guarantees its orthogonality, as well as the implementation of process parameter optimization algorithms based on historical results that compensate for the wear of the drilling bits. Automatic sealing and fastening strategies that involve the measurement of the main fastener quality parameters allow for the complete verification of the entire assembly process of each part. Additionally, an advanced multimodal perception system continuously monitors the collaborative workspace to ensure safe human–robot collaboration (HRC) tasks. Through this integrated architecture, LABOR substantially reduces expenses and facilitates maintenance and programming.

Development of a Minimally Invasive Surgical Robot Using Self-Helix Twisted Artificial Muscles

In the field of surgery, minimally invasive surgical robots (MISRs) have emerged as the persistent pursuit of physicians to minimize harm and perform precise surgery. The structure of newly proposed MISRs tends to change form rigid to flexible, which poses a challenge to precise control. In this work, a MISR actuated by self-helix twisted artificial muscles (SHTAMs) with large bending angle and high precision is developed. The configuration and operation principle of the MISR are illustrated. Then, the physical model of SHTAM and the kinematics model of the end effector are established. The contraction ratio of SHTAM reaches 27.5%, and the output force is 5424.2 mN. Besides, the maximum bending angle (about 92°) of MISR is measured to verify the kinematic analysis. Moreover, in the point positioning control experiments, the steady-state error is less than 0.11°. Subsequently, the trajectory tracking tests on sinusoidal trajectories with different frequencies and amplitudes are carried out, and the circular trajectory tracking experiment is also performed with a maximum error of 1.8° in cold gel environment. The experimental results indicate that the proposed MISR has a large bending angle and can achieve accurate trajectory control, which exhibits excellent prospect in precision minimally invasive surgery.

An Adaptive Control Method and Learning Strategy for Ultrasound-Guided Puncture Robot

The development of a new generation of minimally invasive surgery is mainly reflected in robot-assisted diagnosis and treatment methods and their clinical applications. It is a clinical concern for robot-assisted surgery to use a multi-joint robotic arm performing human ultrasound scanning or ultrasound-guided percutaneous puncture. Among them, the motion control of the robotic arm, and the guiding and contact scanning processes of the ultrasonic (US-) probe determine the diagnosis effect, as well as the accuracy and safety of puncture surgery. To address these challenges, this study developed an intelligent robot-assisted system integrating autonomous US inspection and needle positioning, which has relation to several intelligent algorithms such as adaptive flexible control of the robot arm, autonomous US-scanning, and real-time attitude adjustment of the puncture needle. To improve the cooperativity of the spatial operation of the robot end-effector, we propose an adaptive flexible control algorithm that allows the operator to control the robot arm flexibly with low damping. To achieve the stability and uniformity of contact detection and imaging, we introduced a self-scanning method of US-probe based on reinforcement learning and built a software model of variable stiffness based on MuJoco to verify the constant force and velocity required by the end mechanism. We conducted a fixed trajectory scanning experiment at a scanning speed of 0.06 m/s. The force curve generally converges towards the desired contact force of 10 N, with minor oscillations around this value. For surgical process monitoring, we adopted the puncture needle detection algorithm based on Unet++ to acquire the position and attitude information of the puncture needle in real time. In short, we proposed and verified an adaptive control method and learning strategy by using an UR robotic arm equipped with a US-probe and puncture needle, and we improved the intelligence of the US-guided puncture robot.