Design Of End-effector Research Articles

Vision-guided robotic system for aero-engine inspection and dynamic balancing

The fourth industrial revolution witnessed significant advancements in automating numerous aircraft inspection tasks. Still, certain critical procedures continue to rely on manual execution, including the aero-engine blade weighing process. This task is of paramount importance for blade mass inspection and engine dynamic balancing. Yet, automation of aero-engine blade weighing remains a challenge due to the intricate geometry of engine blades, and the stringent requirements on precision. To address this gap, this paper introduces, for the first time, a vision-guided robotic system for autonomous aero-engine blade weighing. The proposed system presents a novel end-effector design incorporating a high-precision load cell for accurate and rapid weighing coupled with an imaging sensor for autonomous robotic perception capabilities. The system is tested in industrial settings, and the results show a high weighing precision and accuracy of 0.0404 g and of 0.0252 g, respectively. Our system offers the advantage of seamless integration into existing industrial setups without the need for facility reconfiguration. Video Link

Design of a force-controlled end-effector based on the pneumatic artificial muscle for robotic polishing

Purpose Polishing is a crucial process in mechanical manufacturing. The use of industrial robots to automate polishing is an inevitable trend in future developments. However, current robotic polishing tools are too large to reach inside deep holes or grooves in workpieces. This study aims to use a pneumatic artificial muscle (PAM) as the actuator and designs a force-controlled end-effector to reach inside the deep and narrow areas in the workpiece. Design/methodology/approach This approach first addresses the challenge of converting the tensile force generated by the PAM into pushing force through mechanism design. In addition, a dynamics model of the end-effector was established based on the three-element model of the PAM. A combined control strategy was proposed to enhance force control accuracy and adaptability during the polishing process. Findings Experiments were conducted on a robotic platform equipped with the proposed end-effector. The experimental results demonstrate that the end-effector can polish the inner end face of holes or grooves with diameters as small as 80 mm and depths reaching 200 mm. By implementing the combined control strategies, the target force tracking error was reduced by 48.66% compared to the use of the PID controller alone. Originality/value A new force-controlled end-effector based on the PAM is designed for robotic polishing. According to the experimental result, this end-effector can polish not only the outer surfaces of the workpiece but also the internal surfaces of workpieces with deep holes or grooves specifically. By using the combined control strategy proposed in this paper, the end-effector significantly improves force control precision and polishing quality.

Bioinspired design and validation of a soft robotic end-effector with integrated shape memory alloy-driven suction capabilities

The exploration of adaptive robotic systems capable of performing complex tasks in unstructured environments, such as underwater salvage operations, presents a significant challenge. Traditional rigid grippers often struggle with adaptability, whereas bioinspired soft grippers offer enhanced flexibility and adaptability to varied object shapes. In this study, we present a novel bioinspired soft robotic gripper integrated with a shape memory alloy (SMA) actuated suction cup, inspired by the versatile grasping strategies of octopus arms and suckers. Our design leverages a tendon-driven composite arm, enabling precise bending and adaptive grasping, combined with SMA technology to create a compact, efficient suction mechanism. We develop comprehensive kinematic and static models to predict the interaction between arm bending deflection and suction force, thereby optimizing the gripper's performance. Experimental validation demonstrates the efficacy of our integrated design, highlighting its potential for advanced manipulation tasks in challenging environments. This work provides a new perspective on the integration of bioinspired design principles with smart materials, paving the way for future innovations in adaptive robotic systems.&#xD.

Calibration and experiments of discrete element flexible model parameters for kiwifruit stalk

A method combining experimental and simulation optimization was used to calibrate parameters to enhance the accuracy of discrete element model parameters during kiwifruit stem separation. First, physical experiments were conducted to determine the intrinsic and contact parameters of kiwifruit stalk. Second, the mechanical parameters of the kiwifruit stalks were determined using three-point bending and shear tests. On this basis, simulation tests were conducted on kiwifruit stalks by combining the Hertz-Mindlin model with a bonding model, and the optimal combination of bonding parameters was confirmed using the bending strength and maximum shear force. Finally, a discrete element model of the kiwifruit was built with the determined bonding parameters and simulated, and the reliability of the model was verified through mechanical tests. The results showed that the density was 867.5 kg/m3, Poisson's ratio was 0.26, the modulus of elasticity was 3.25 × 108 Pa, the recovery coefficient between the fruit stalks and steel parts was 0.365, and the average values of the static and dynamic friction coefficients between the kiwifruit stalks and steel parts were 0.268 and 0.152, respectively. The kiwifruit stem bonding parameters were normal stiffness per unit area kn=7.201×1011 N/m3, shear stiffness per unit area kt=2.379×1011 N/m3, critical normal stress σmax=5.937×108 Pa, critical shear stress tmax = 2.354×109 Pa, and bonded disc radius Rj=0.164 mm. Compared with the results of the mechanical tests, the relative errors of the bending strength and maximum shear of the discrete element model were 2.13% and 2.84%, respectively. The results showed that the discrete element model improves the simulation of the bending and shearing processes of kiwifruit stalks and is capable of characterizing the physical properties of kiwifruit stalks. The results of this study provide a theoretical foundation for the optimal design of end effectors.

Design of a Novel Passive Polishing End-Effector With Adjustable Constant Force and Wide Operating Angle

Design of a Novel Passive Polishing End-Effector With Adjustable Constant Force and Wide Operating Angle

Combining finite element analysis and reinforcement learning for optimal grip point planning of flexible components

Abstract Handling large flexible components is still a challenge in many industries. Examples include the handling of fibre-reinforced plastics or the assembly of industrial-scale electrolytic cells. Difficulties often arise in the design of suitable endeffectors. Inefficient gripping point design, i.e. the total number and positioning of grippers, can lead to increased stress and deflection of the component being handled. To counteract this, endeffectors are often oversized resulting in the use of more grippers than needed. Correspondingly, heavier moving masses imply longer handling times as well as higher energy consumption. This paper presents a process for planning and optimising gripping points for large flexible components. In addition to the shape of the component, actual dynamic loads of the handling path are also taken into account. The key element to the process is an optimisation algorithm based on reinforcement learning and trained using an finite element method (FEM) simulation. After computing a desirable starting configuration, the algorithm optimises the placement of gripper positions while aiming for a reduced total number. In addition, the optimisation has prescribed handling limits, such as physical and geometric constraints, that must not be exceeded. It was shown that the algorithm satisfactorily optimises the gripping points for dynamic loads for different materials and shapes. Furthermore, it has been shown that the computation of an initial configuration yields preferable results for simple components, yet requiring optimisation in the case of more complex shapes.

Design and Fabrication of SCARA for Image Processing in Industry

The scope of our project is the design and fabrication of SCARA (Selective Compliance Articulated Robot Arm) robots optimized for image processing tasks within industrial environments. This report presents a comprehensive review of the design, control, and applications of SCARA robots, focusing on their integration with image processing technologies to enhance industrial automation. We delve into the underlying principles governing the kinematics and dynamics of SCARA robots, elucidating their operational mechanisms and capabilities. Advancementsin end-effector design and sensor integration have enhanced the adaptability of SCARA robots, enabling them to tackle complex tasks in unstructured environments.

Key Technologies for Autonomous Fruit- and Vegetable-Picking Robots: A Review

With the rapid pace of urbanization, a significant number of rural laborers are migrating to cities, leading to a severe shortage of agricultural labor. Consequently, the modernization of agriculture has become a priority. Autonomous picking robots represent a crucial component of agricultural technological innovation, and their development drives progress across the entire agricultural sector. This paper reviews the current state of research on fruit- and vegetable-picking robots, focusing on key aspects such as the vision system sensors, target detection, localization, and the design of end-effectors. Commonly used target recognition algorithms, including image segmentation and deep learning-based neural networks, are introduced. The challenges of target recognition and localization in complex environments, such as those caused by branch and leaf obstruction, fruit overlap, and oscillation in natural settings, are analyzed. Additionally, the characteristics of the three main types of end-effectors—clamping, suction, and cutting—are discussed, along with an analysis of the advantages and disadvantages of each design. The limitations of current agricultural picking robots are summarized, taking into account the complexity of operation, research and development costs, as well as the efficiency and speed of picking. Finally, the paper offers a perspective on the future of picking robots, addressing aspects such as environmental adaptability, functional diversity, innovation and technological convergence, as well as policy and farm management.

Design and development of a peduncle-holding end effector for robotic harvesting of mango

Design and development of a peduncle-holding end effector for robotic harvesting of mango

Innovative integration of maturity detection and robotic technology for enhanced litchi harvesting

Abstract An integrated approach marries an optimized YOLOv7 deep learning model with a 6-axis robotic arm, featuring a novel end-effector design, to elevate automated litchi harvesting. The model, refined with ACmix attention and Focal-EIoU loss functions, adeptly identifies litchi maturity across diverse orchard settings, overcoming challenges like variable lighting and occlusions. Rigorous field validations and real-world applications demonstrate the system’s efficacy, with an 85.7% success rate in precisely harvesting mature litchis. This fusion of cutting-edge image recognition with strategic mechanical innovation effectively mitigates labor shortages and enhances productivity, marking a significant leap forward in orchard automation.

AN EXPERIMENTAL INVESTIGATION ON NOVEL SEGMENTED OMNI WHEELED HYBRID MOBILE ROBOT TO ASSESS OBSTACLE CLIMBING CAPABILITY

Abstract This article introduces a novel quadrupedal hybrid mobile robot with a segmented omni wheel design capable of climbing obstacles of height greater than its wheel radius. The unique wheel design comprises of two parallel coaxial 240-degree segmented omni wheels per leg with independent offset angle control. The transformation from wheel to leg mode and vice versa can be seamlessly achieved by controlling the offset angle between the segmented omni wheels. A series of experiments are carried out to evaluate the robot's performance for obstacle climbing capability utilizing various wheel end effector designs, and a comparative analysis is presented. The results indicate that the obstacle climbing capability of segmented omni wheel design with zero offset angle is improved by 40.7% compared to standard wheel and the unique wheel design configuration facilitates seamless staircase climbing capability without any complex control scheme. In addition, statistical studies using Taguchi method and ANOVA are performed on the experimental findings. A linear regression model to predict power consumption has been developed and the significant factors influencing the robot's power consumption and stability are presented.

Design and development of universal soft robotic end effector through machine learning on the IRB 360 robot

Design and development of universal soft robotic end effector through machine learning on the IRB 360 robot

Exploring Kinematic Bifurcations and Hinge Compliance for In‐Hand Manipulation: How Could Thick‐Panel Origami Contribute?

Origami‐inspired mechanisms have found significant applications in end effector design. So far, the exploration of thick‐panel origami has been relatively limited, but it is worth noting that the incorporation of rigid thick panels can introduce unique mechanical properties, showcasing great potential in addressing manipulation challenges. Our previous work has developed a gripper from thick‐panel waterbomb origami, which can pick up a variety of daily objects. Based on the same prototype, this article extends the gripper's function from grasping to in‐hand manipulation, which is attributed to the kinematic bifurcations and compliance of thick‐panel origami. A kinematic study is carried out to investigate the gripper's bifurcated motion modes. The hinge compliance is also taken into account to enhance the gripper's motion dexterity. Theoretical analysis and experiments are conducted to demonstrate both features, thereby paving the foundation for achieving dexterous motions with a simplified control strategy. Aided by a differential mechanism, the gripper can effectively interact with objects with the actuation inputs from only two motors. Objects including balls, cuboids, and cones are explored for in‐hand manipulation under different motion modes, showing varied trajectories. With the integration of tactile sensors at the fingertips, we have also revealed the gripper's potential for classification tasks.

A Wearable Haptic Device for the Hand With Interchangeable End-Effectors.

This article presents a 4-degrees-of-freedom (4-DoF) hand wearable haptic device for Virtual Reality (VR). It is designed to support different end-effectors, that can be easily exchanged so as to provide a wide range of haptic sensations. The device is composed of a static upper body, secured to the back of the hand, and the (changeable) end-effector, placed in contact with the palm. The two parts of the device are connected by two articulated arms, actuated by four servo motors housed on the upper body and along the arms. The article summarizes the design and kinematics of the wearable haptic device and presents a position control scheme able to actuate a broad range of end-effectors. As a proof of concept, we present and evaluate three representative end-effectors during interactions in VR, rendering the sensation of interacting (E1) with rigid slanted surfaces and sharp edges having different orientations, (E2) with curved surfaces having different curvatures, and (E3) with soft surfaces having different stiffness characteristics. A few additional end-effector designs are discussed. A human-subjects evaluation in immersive VR shows the broad applicability of the device, able to render rich interactions with a diverse set of virtual objects.

Design and Simulation of End Effector for Young-Pear-Bagging Robot

In order to address the time-consuming and labor-intensive challenges as well as the suboptimal operational quality encountered in the conventional processes of fruit bagging within expansive orchards, an innovative end-of-bagging actuator is proposed, which can be installed on a fruit-production robot. Due to the excessive power sources required to complete the bagging operation, while also taking into account the quality and cost of the end effector, we have implemented a clutch transmission system to control individual motors, thereby achieving efficient bag-opening and collection actions. Through kinematic analysis of the bagging end effector, the optimal bag opening size is determined to be 40.3372 mm, with a deviation of 0.1428 mm from the design target and an error rate of 0.35%. This ensures the desired bag size for bagging juvenile fruits. Moreover, a dynamic simulation model comprising rigid drive components and a flexible clutch was developed. The simulation results demonstrate the system’s stable performance. However, it is evident that the gear speed falls below that of the flexible clutch, resulting in insufficient bag opening and bag gathering compared to the intended design target. The observed phenomenon is a result of the characteristics exhibited by the flexible clutch. Specifically, the demands for bagging and stretching can be accommodated by modifying the stiffness and geometric configuration of the flexible clutch, alongside the level of operational force. To conclude, the suggested end effector can successfully simulate the implementation of the manual bagging process. By taking into account the quality and cost of the end effector, a clutch drive system was utilized to regulate a single motor, resulting in efficient bag-opening and collection actions. This approach offers a more integrated and efficient solution compared to manual bagging and semi-automatic mechanically assisted bagging methods.

Selection and Design Process for End-Effectors

Due to increasing economic competition, many companies are automating their production processes by means of handling systems. One very important component of any handling system is the end-effector, as it comes into direct contact with the handling object. Therefore, selecting and designing the best end-effector is of enormous importance for the safe and successful operation of handling systems. This paper presents a concept of a process for the systematic selection and design of end-effectors. The concept presented here exemplified for vacuum suction grippers. A first implementation showed the feasibility of the concept.

Design of an Intelligent Pear Bagging End-Effector Based on Yolov8 and SGBM Algorithm

Design of an Intelligent Pear Bagging End-Effector Based on Yolov8 and SGBM Algorithm

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.

Design and experiment of a shovel-tooth removal end-effector for abnormal plants in hybrid rape breeding based on MBD-DEM coupling.

In view of the problem that removing abnormal plants in breeding rape requires a large amount of labor and is inefficient, combined with the planting requirements of breeding rape, a shovel-tooth end-effector was designed, and a shovel-tooth removal test bench was built. A simulation model based on MBD (Multibody Dynamics)-DEM (Discrete Element Method) coupling was constructed. Then we conducted a Box-Behnken test with four factors and three levels. Taking the angle of soil penetration, speed of soil penetration, depth of soil penetration and speed of shovel-tooth gathering as the test factors, the soil penetration force and shovel-tooth gathering force as the test indicators. The mathematical regression model between test indicators and test factor was established. After optimizing the parameters of the model, the best combination of parameters with low soil penetration force and low shovel-tooth gathering force was obtained: angle of soil penetration of 84°, speed of soil penetration of 9 cm/s, depth of soil penetration of 8cm, and speed of shovel-tooth gathering of 6 cm/s. The simulation model was validated by field experiments. The average soil penetration force and average shovel-tooth gathering force of the three groups of pull-out tests were 34.8 N and 763.0 N, respectively. The removal rates were 96%, 92%, and 94%, all greater than 90%, indicating that the removal effect of the shovel-tooth end-effector was good, and the parameters were reasonably designed. The results can serve as reference for the design of rape abnormal plants removal device and the operation of MBD-DEM coupling simulation end-effector.

Study on Mechanical Properties of Tomatoes for the End-Effector Design of the Harvesting Robot

Agricultural robotics has emerged as a research area within robotics, with a particular focus on designing end effectors that are adapted to the physical characteristics of the target fruits. Acquiring a comprehensive understanding of the physical and mechanical properties specific to tomato fruits not only minimizes mechanical damage during grasping processes but also serves as a foundation for the optimal design of gripping components. In this study, the Syngenta Sibede variety of tomatoes was used as the experimental material. The reversible viscoelastic behavior and deformation characteristics of tomato fruits were approximated using a four-element Burgers model through creep testing. The fitting coefficients for the model exceeded 0.99. The creep parameters for the four ripening stages of tomatoes were obtained, and the correlation between the ripening stage, deformation value, and creep parameters was analyzed. Correlation analysis was performed to examine the relationships between each parameter and creep deformation, revealing significant and highly significant correlations. Inter-parameter correlations were also found to be highly significant. Puncture tests were conducted on tomatoes. The exocarp rupture force of the green-ripening stage was 9.224 ± 0.901 N, which was 53.87%, 70.63%, and 104.01% higher than that of the semi-ripening stage, early firm-ripening stage, and mid-late firm-ripening stage, respectively. This study suggests that when harvesting tomatoes at the semi-ripening stage and beyond, attention should be paid to trimming the stem. Compression experiments were conducted on tomatoes, and it was discovered that under the same ripening stage, the axial compressive rupture force of tomatoes was greater than the radial rupture force. Tomatoes exhibited anisotropic behavior. The grasping direction is axial, which can be used as the new design direction of the end-effector.