End-effector Research Articles

Fixed‐time dual sliding mode control for linear synchronous motor maglev systems

AbstractA dual fixed‐time terminal sliding mode control strategy is proposed to address the problems of magnetic coupling, end effects and unknown disturbances in linear synchronous motor maglev systems, which ensures that the system tracking trajectory achieves fixed‐time convergence and high accuracy. First, a fixed‐time integral terminal sliding mode surface is designed to obtain the desired dynamic properties and avoid the singularity problem. Second, based on the dynamic sliding mode theory, a second fixed‐time terminal sliding mode surface is designed to weaken the chattering problem in the controller by replacing the discontinuous switching signal with a continuous switching rule. The proposed controller is theoretically proved to be fixed‐time convergent and the convergence time is independent of the initial conditions by means of the Lyapunov function and the fixed‐time convergence theorem. Finally, simulations and experiments are carried out on a linear maglev experimental platform. Compared with the fixed‐time sliding mode control, the simulation and experimental results show that the proposed strategy improves the tracking accuracy by 37.5%, the convergence speed by 33.3%, and the robustness by 42.1%, which has the advantages of fast convergence speed, strong robustness, and weak chattering.

Training in problem solving in kinematics at a modern children’s technology park

The article describes the issues of development and programming of robot manipulators based on robotics kits in a children’s technology park. It covers the fundamental knowledge elements from mathematics and mechanics for solving direct and inverse kinematics problems. A manipulator consists of several links and an end effector, which form kinematic pairs performing translational or rotational movements relative to each other. The direct kinematic problem involves calculating the coordinates of the end effector given the known values of the joint angles, while the inverse kinematics problem is the opposite, calculating the joint angles of the manipulator given the known coordinates of the end effector. Solving these problems requires knowledge of basic coordinate systems, the Pythagorean theorem, trigonometric functions and the cosine theorem, all of which are described in the article. The ability to solve kinematics problems is crucial for successful manipulator programming as a whole. The article also provides an example of converting step motor steps into end effector coordinates and discusses the dependence of manipulator accuracy on the characteristics of the step motor.

A novel apparent permeability model for shale considering the influence of multiple transport mechanisms

Changes in pore pressure during the extraction of shale gas lead to dynamic alterations in the pore structure and permeability, making it challenging to gain a comprehensive understanding of the flow behaviors of shale gas. The pore structure of shale is complex, with a variety of storage modes and gas transport processes constrained by a number of factors. For instance, when gas flows through a transport channel with a finite length, it is imperative to take into account the flow loss caused by the bending of inlet and outlet streamlines, prior models typically neglect the impact of end effects, resulting in an exaggerated estimation of the shale permeability. Furthermore, a decrease in pore pressure corresponds to an increase in the Knudsen number, resulting in the breakdown of the continuity assumption of the Navier–Stokes equation, this signifies the gradual shift of the transport regimes from continuum flow to other transport regimes. The gas flow process is nonlinear due to the alternating impact of multicomponent transport mechanisms and various microscale effects. In this paper, we presented a novel apparent permeability model for shale that incorporates the impact of real gas effect, end effects, transport regimes, adsorption, and effective stress. First, we assumed the channel for shale gas transport to be circular pore and calculated the viscosity under the influence of a real gas effect as well as the corresponding Knudsen number. Subsequently, building upon the foundation of the slip model, we introduce the influence of the end effects to establish a bulk phase permeability for shale, further considering the impact of surface diffusion. Then, the pore radius was quantified under the influences of adsorption and effective stress. Using the intrinsic correlation between permeability and pore radius as a bridge, a shale apparent permeability model was further derived. The model encompasses various transport regimes and microscale effects, replicating the gas flow behaviors in shale. The new model was verified through comparison with published experimental data and other theoretical models, while analyzing the evolution of apparent permeability. Additionally, this paper discusses the influence of various factors, including end effects, pore radius, internal swelling coefficient, sorption-induced strain, and model-related parameters on the shale apparent permeability.

Direct electromagnetic force control of linear induction motor with end effects using fuzzy controller

In this article is a present dynamic model of a linen induction motor with end effects, occurs when the electromagnetic system of the motor is open. Instead of the angular speed and electromagnetic torque as a rotation motor, in the linear induction motor we have linear speed and linear electromagnetic force, which are sufficiently influenced by the open electromagnetic system of the primary and secondary elements of the linear motor. The choice of an appropriate control system for a linear induction motor is of particular importance considering the use of this type of motor in manufacturing. There are different types of control schemes for standard rotary motors that have their own advantages and disadvantages. When choosing a motor control scheme, we strive to achieve the following parameters, such as smoothness of regulation, ability to regulate in all four quadrants, accuracy of regulation, range of regulation and last but not least, simplicity of regulation. One such method that meets these criteria for rotary motors is the direct torque control method with space vector modulation. The control system of the linear induction motor proposed in this paper is based on this method, taking into account the open electromagnetic system and the occurrence of the end effects of the linear induction motor. Instead of the angular reference velocity as a rotary motor, in this case we have a linear reference velocity to the input, which is compared to the current linear velocity of the motor. The present paper also uses the vector modulation method by analogy with direct torque control with space vector modulation of the rotary motor. For the conversion of a linear velocity to a linear electromagnetic force, instead of a standard PI controller, it is using a fuzzy controller to convert a linear velocity to a reference electromagnetic force.

Visual Servo Control for Workspace Navigation of Nanorobot End-Effector Inside SEM

Despite of the promising advancements in the last decade, the majority of scanning electron microscope (SEM)-based nanomanipulation tasks remain manually performed. Even in automated tasks, human intervention is required, at least during the task preparatory stage, where both the object of interest and robot end-effector are adequately enclosed in the field of view (FOV) of SEM at moderate magnification. This paper proposes a fully automated visual servo control method for workspace navigation of nanorobot end-effector that actively maintains the end-effector position offset from the center of FOV during passive working scene zooming and translation operations. We also propose using the scaling image Jacobian matrix theory to adaptively establish the hand-eye relationship of the nanorobotic system at uncalibrated magnifications, without the need for hardware regulation. This proposed method for workspace navigation is applicable to almost all commercial nanomanipulation systems. To the authors’ best knowledge, there has been no dedicated research on this problem in the literature. Experiments show that the proposed method significantly improves workspace navigation efficiency by about two-thirds, even for a skilled operator. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Workspace navigation refers to the process of moving the FOV to visually enclose the object or feature of interest at a moderate magnification, which is prerequisite for initializing either an automated or manual nanomanipulation task. This process involves consecutive zooming of the SEM in and out, as well as translating the sample stage, which can cause the end-effector to move out of the FOV. Therefore, it is necessary to move the robot end-effector with visual assistance along workspace navigation to avoid unexpected collisions. Typically, skilled operators perform this process manually in almost all nanomanipulation tasks, which is tedious and time-consuming. Therefore, developing an automated visual servo control method for workspace navigation of end-effector will significantly contribute to the nanomanipulation community.

Design of a wearable shoulder exoskeleton robot with dual-purpose gravity compensation and a compliant misalignment compensation mechanism.

This paper presents the design and validation of a wearable shoulder exoskeleton robot intended to serve as a platform for assistive controllers that can mitigate the risk of musculoskeletal disorders seen in workers. The design features a four-bar mechanism that moves the exoskeleton's center of mass from the upper shoulders to the user's torso, dual-purpose gravity compensation mechanism located inside the four-bar's linkages that supports the full gravitational loading from the exoskeleton with partial user's arm weight compensation, and a novel 6 degree-of-freedom (DoF) compliant misalignment compensation mechanism located between the end effector and the user's arm to allow shoulder translation while maintaining control of the arm's direction. Simulations show the four-bar design lowers the center of mass by cm and the kinematic chain can follow the motion of common upper arm trajectories. Experimental tests show the gravity compensation mechanism compensates gravitational loading within Nm over the range of shoulder motion and the misalignment compensation mechanism has the desired 6 DoF stiffness characteristics and range of motion to adjust for shoulder center translation. Finally, a workspace admittance controller was implemented and evaluated showing the system is capable of accurately reproducing simulated impedance behavior with transparent low-impedance human operation.

Automated Manufacturing of Grid Stiffened Panels with Radically Reduced Tooling

Grid stiffened continuous fiber reinforced composite panels are an attractive option for creating lightweight structures due to the tailorability for various applications and the resulting high specific properties. However, the panel stiffeners and stiffener intersections result in high tooling complexity and correspondingly high cost of implementation. These factors have limited the impact of such structures in the composites industry. Previous research has demonstrated the ability to produce high quality, high aspect ratio beams, representative of individual grid stiffeners, using E-glass/PET comingled tow via direct digital manufacturing. Further, prior preliminary efforts have demonstrated the potential to use the same approach to manufacture grid intersections that have continuous fiber in both directions. To expand on the previous efforts in grid stiffeners produced by direct digital manufacture with radically reduced tooling requirements, this effort compares two methods of providing positioning and consolidation, nozzle vs. roller. Both processes are based on a commingled yarn feedstock. The extrusion through a nozzle has been shown to enable grid intersection control through local variations in applied consolidation and serves as the baseline process. However, this approach requires a continuous placement path to create the complete grid stiffened panel as no mechanism for cutting and restarting has been implemented. Alternatively, a newly developed placement head incorporating cut and refeed, mounted to a 6-axis robot, offers the potential of improved path placement efficiency. The two techniques are used to produce similar grid composite stiffeners to evaluate the effectiveness of producing the grid intersections. Rate of deposition of the two end effectors are compared and the quality of the associated grid stiffeners, and intersections, are determined through measurement of geometry, fiber volume fraction and void fraction.

Approach of Automated Robot Arrangement in Manufacturing Cells

Implementing industrial robots in manufacturing cells for automation requires specialized knowledge. Trajectory planning and end-effector design significantly increase the required effort. The trajectory planning is iterative and time-consuming and also depends on the robot base placement, which is why the automation of robot base placement is being explored. This paper presents a novel approach to automate the robot base positioning demonstrated on the example of the Central Research Center 1153 (CRC 1153) Tailored Forming. Accordingly, a three-step approach is developed: First, an accurate 3D environment has to be created to define the forging cell structure, otherwise problems may occur during the transition to the real-world application. Next, the robot’s position and trajectory are calculated and optimized using a proprietary algorithm. If there is no arrangement that allows collision-free trajectory planning, another algorithm is applied that extends the robot’s workspace by adjusting the arrangement of the robot’s flange and the tool center point (TCP) of the end effector. Finally, AI-based methods are used to equip the end-effector and the robot with customized coupling elements depending on the TCP adjustment performed in the previous step. As a result of this work, a framework for automated robot placement in manufacturing cells using optimization algorithms and AI-based methods is presented. This increases the efficiency of automated manufacturing cell design and minimizes the dependency of the result’s quality on the engineer’s experience.

A Nonlinear 3-D Hybrid Model for Surface-Mounted Permanent Magnet Machines Considering End Effect

A Nonlinear 3-D Hybrid Model for Surface-Mounted Permanent Magnet Machines Considering End Effect

Specific Object Picking Robotic Arm Using Haar Cascades

This project shows a robotic arm that can pick up objects. It was made with accuracy and speed in mind for use in factories. The robotic arm is very good at picking up metal nuts. It uses cutting edge technologies, like Haar cascade to find objects and inverse kinematics to figure out angles very accurately, to make its moves more exact and dexterous. A powerful computer vision method called Haar cascade is used to find metal nuts in the robotic arm's working environment. To do this, positive and negative pictures are used to train a Haar cascade classifier, which makes a model that can recognize the unique traits of metal nuts. The object recognition process makes sure that the nuts are located correctly, which lets the robotic arm deal with them in a controlled and precise way. The robotic arm uses inverse kinematics along with Haar cascading to figure out the exact joint angles needed for smooth, controlled movement. Inverse kinematics is very important for figuring out the joint setups that are needed to place the robotic arm's end-effector exactly on top of the metal nuts that have been found. Haar cascading for finding objects and inverse kinematics for accurate angle estimates work together to make sure that the robotic arm can pick up metal nuts in a variety of space arrangements. This combined system is a high-tech way to automatethe picking of specific items in manufacturing and assembly lines. It shows how industrial automation can be used to improve accuracy, efficiency, and flexibility.

Design of Key Technologies for Robot End Effectors

Design of Key Technologies for Robot End Effectors

On intelligent object sorting and assembly: versatile end-effector for robotized handling of electrical components

In the ever-evolving landscape of industrial automation, versatile and ‘smart’ robotic solutions for sorting and assembly operations have become increasingly important. The diversity of product variants in terms of size, geometry, material and texture increases the complexity of the tooling needed for robot handling during assembly. To mitigate this challenge, this study presents a novel design of a versatile and cost-effective robot end-effector, to sort out products from a stack of multi-variant objects and assemble them with minimal re-grasping adjustments. The proposed smart adaptable gripper is equipped with multiple suction heads, each with independent triggering capabilities, enabling the end-effector to adapt to diverse parts’ geometry. A vision-based system has also been integrated to the gripping system enhancing it with perception capabilities. A two-step approach is employed to address the kitting to assembly problem from start to end utilising real-time pixel-wise grasp quality analysis in combination with gripper’s masks convolution for optimized grasping. The performance of the proposed framework in terms of the design functionality is evaluated in a case study involving the manipulation and assembly of electronics on a control panel derived from the elevators’ manufacturing industry.

LLM for Differentiable Soft Robotic Vision Objects Manipulation

Most existing neural soft object manipulation systems rely on differentiable simu- lation as the default physics engine. However, current explicit differentiable sim- ulation solvers adopt a heuristic searching approach to manipulate the soft body, which easily gets stuck when the initial stage of the end effectors is sub-optimal on single-stage tasks or when performing multi-stage tasks that require complex hi- erarchical actions, which often leads to local-minima. Furthermore, existing deep soft object manipulation systems never consider the soft multi-body dynamics and model the dynamic system with naive explicit visual cues (e.g., image frame). To address this challenge, we propose an implicit, i.e., with energy-based models, soft objects manipulation differentiable simulator (iDSoftor) that guides the dif- ferentiable physics solver to deform the various soft object. The key idea of our work is to integrate energy-based models into the soft-object differentiable simu- lation to address the local minima in common explicit (heuristic transport-based) methods to stabilize the gradient of training differentiable simulators. On simple tasks, such as one-stage tasks, our proposed method can feasibly find a suitable initial stage based on theoretical arguments, refer to. On complex multi-stage tasks with multimodal, like implicit visual cues states, our proposed methods can iteratively adjust the manipulation trajec- tory from the perspective of energy priorities. To evaluate the feasibility of our proposed method, we formulate various potential novel soft-object manipulation tasks and demonstrate a preliminary story.

Robotic Fast Dual-Arm Patch Clamp System for Mechanosensitive Excitability Research of Neurons.

A robotic fast dual-arm patch clamp system with controllable mechanical stimulation is proposed in this paper for mechanosensitive excitability research of neurons in brain slice. First, a kinematic model of a dual-arm patch clamp system combined with Monte Carlo method is developed to calculate the workspaces of recording micropipette and stimulation micropipette, and optimize the length of end effector for reducing collision incidences during operation. Then, a quantitative stimulation method to cells using one micropipette is developed based on pressing depth control. Finally, a fast robotic dual-arm patch clamp operation process is proposed based on a three-stage motion control of dual micropipettes to approach target cells and form whole-cell recording with quantitative mechanical stimulation. Experimental results on 50 pyramidal neurons in the primary visual cortex of mouse brain slices demonstrate that this system achieves a threefold throughput with a 37% improvement in the success rate of the contact process and a 42% improvement in the success rate of whole-cell recording in comparison to manual operation. With these advantages, a mechanical stimulation-regulated increase in neuron excitability is observed in primary visual cortex. The experimental results also show that the sodium ion current may be more sensitive to mechanical stimulation than potassium ion current. Our system significantly improves the efficiency of mechanical stimulation induced excitability research of neurons in brain slices. Our methods have the potential to investigate pathological and pathogenic mechanisms of mechanosensitive ion channel dysfunction-induced diseases in the future.

Noise-Suppressing Newton Algorithm for Kinematic Control of Robots

In this paper, armed with the integral control method, a new noise-suppressing Newton (NSN) algorithm is proposed for the redundancy resolution of redundant robot manipulators efficiently. For practical hardware implementation, the discrete-time noise-suppressing Newton (abbreviated as DTNSN) algorithm is discretized from the continues NSN algorithm. Specifically, the distinguishing feature of the proposed DTNSN algorithm is that it can rigorously converge with inherent tolerance to noises induced by communication jamming and computational systematical errors. In contrast, considerable traditional algorithms often dispose of noises with the high-degree filter from the viewpoint of signal processing, which requires a complex system structure and further results in a heavy computational burden. Note that theoretical analyses are provided to elaborate the convergent property of the DTNSN algorithm polluted with constant bias, time-dependent linear noises and bounded random noises. Besides, by the proposed DTNSN algorithm, the end effector of both serial and parallel redundant robot manipulators complete the allocated motion planning and are impervious to the noisy simulated environment.

Kinematic Analysis of 3-PRPPS Spatial Parallel Manipulator with Circularly Guided Base for Singularity-Free Robotic Motions

Robot manipulators are classified as serial manipulators and parallel manipulators. Parallel manipulators are classified into planar and spatial parallel manipulators (SPMs). The parallel manipulators have moved and fixed platforms connected with serial chains. The parallel manipulators have many linkages, which create a singularity problem. The singular positions of SPMs have also gained substantial attention in various industrial applications due to their intrinsic advantages in precision, flexibility, and load-bearing capabilities. The 3-PRPPS SPM has three prismatic joints, one spherical joint, and one revolute joint. This work changed the fixed base with a circular guided base to avoid singularity issues. The manipulator was modeled with direct kinematic relations. The Jacobian matrix for position and orientation was derived. The workspace was taken as the common area of the three circles, whose radius was the maximum arm length. The position and orientation of the end effector were traced. In the form of the end effector traces, no singularities in the mechanism were observed. The path of the robot manipulator was observed in all the possible positions and orientations. The multi-body simulation was also conducted on the 3-PRPPS manipulator, the main findings of which are presented in this article.

Motion Hysteresis Compensation Based on Motor Current Segmentation for Elongated Cable-Driven Surgical Instruments

Cable-driven surgical instrument is a reusable and disposable component of Robot-assisted Minimally Invasive Surgery, and it is time-consuming to identify the motion hysteresis compensation model of each instrument in large-scale identification. Besides, the identification results failure caused by the loss of cable tension or lubrication conditions during repeated usage interferes with the accuracy of motion hysteresis compensation. To simplify the identification process and lengthen the instrument life, this paper leverages the relationship between actuate motor current and hysteresis phases, developing a novel motion hysteresis compensation method to compensate the motor reference trajectory. Firstly, prior knowledges including motor current and hysteresis curves of several instruments are collected to train the Hysteresis Identification model and Curve Generation model. Once the two models are well-trained in practical use, the only sensor data in need is the motor current for the Hysteresis Identification model, and the compensation curve will be generated pertinently for the instrument under current use. Finally, Feedforward Compensation scheme is conducted to compensate the reference trajectory of the actuate motor. Experiments study the range of hysteresis compensation errors when the method is applied to numerous surgical instruments with different motion hysteresis, and the feasibility and accuracy are verified. The method can be potentially applied to a wide range of cable-driven mechanisms facing the problem of large-scale identification or the identification results failure after repeated use. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper proposes a feasible motion hysteresis compensation method for cable-driven mechanism (CDM). For some CDMs like elongated cable-driven surgical instrument, their motion hysteresis characteristics will change during repeated use, and their distal angle and cable tension are not available in the environment of use. In these cases, the proposed method enables re-identification because the distal angle or cable tension are not needed during the practical use of our method. Besides, it is easy and low-cost for large-scale identification due to the simplicity of identification procedure. Once the Hysteresis Identification model and Curve Generation model are trained using the pre-collected prior knowledge including motor current and the angle of the end effector, the only sensor data in need to identify and compensate a certain CDM is the its motor current. Then, the pertinent compensation curve for the CDM device can be generated for the actuate motor to follow. The experimental results reveal that the competitive performance with other state-of-the-arts can be achieved. In the future research, we will integrate dynamic characteristics of CDM into the method to expand the scope of application.

Biomimetic learning of hand gestures in a humanoid robot.

Hand gestures are a natural and intuitive form of communication, and integrating this communication method into robotic systems presents significant potential to improve human-robot collaboration. Recent advances in motor neuroscience have focused on replicating human hand movements from synergies also known as movement primitives. Synergies, fundamental building blocks of movement, serve as a potential strategy adapted by the central nervous system to generate and control movements. Identifying how synergies contribute to movement can help in dexterous control of robotics, exoskeletons, prosthetics and extend its applications to rehabilitation. In this paper, 33 static hand gestures were recorded through a single RGB camera and identified in real-time through the MediaPipe framework as participants made various postures with their dominant hand. Assuming an open palm as initial posture, uniform joint angular velocities were obtained from all these gestures. By applying a dimensionality reduction method, kinematic synergies were obtained from these joint angular velocities. Kinematic synergies that explain 98% of variance of movements were utilized to reconstruct new hand gestures using convex optimization. Reconstructed hand gestures and selected kinematic synergies were translated onto a humanoid robot, Mitra, in real-time, as the participants demonstrated various hand gestures. The results showed that by using only few kinematic synergies it is possible to generate various hand gestures, with 95.7% accuracy. Furthermore, utilizing low-dimensional synergies in control of high dimensional end effectors holds promise to enable near-natural human-robot collaboration.

3-D Analytical model of the End Effect in the Transverse Flux Linear Synchronous Motor for Maglev vehicle with Pitch Angles

3-D Analytical model of the End Effect in the Transverse Flux Linear Synchronous Motor for Maglev vehicle with Pitch Angles

柔顺障碍环境下收获甜椒末端执行器的设计与试验

Picking sweet peppers by hand is often time-consuming and laborious. To overcome this, in the current study, we developed an end effector for mechanized and non-destructive harvesting of sweet pepper. The design includes grip modules, shear modules and control systems. Based on the establishment of an approximate mathematical model of sweet pepper fruit and the analysis of the biomechanical characteristics of sweet pepper fruit, a pinch finger was proposed. The proposed mechanism is able to successfully achieve non-destructive and stable fixation of sweet pepper and fruit bunches. Key parameters of peduncles cutting were obtained by the cutting test. A cutting mechanism was then designed to achieve efficient separation of the fruit and fruit stem. The designed end effector achieves precise control through a single-chip microcomputer and multi-sensor integrated control system to achieve mature target fruits. The test results showed that the picking success rate, damage rate and picking time of peppers were 93.3%, 1.6% and 5 seconds, respectively. The end effector designed for sweet pepper picking has a simple and reliable structure, which provides a reference for further research on sweet pepper picking robots.