End-effector Of Robot Arm Research Articles

Visual Servo Algorithm Of Robot Arm For Pick And Place Application

The robot arm is a device consisting of a moving chain of links connected by joints. Electrical motors are frequently used to move each robot arm joint. An end-effector that can move freely in space is usually attached to one end of the robot platform, which is fixed. Robot arms can do repetitive operations at rates and precision far exceeding human operators. Nowadays, robot arm systems are widely used worldwide to increase the quality and efficiency of the manufacturing process in the industry. Typical applications of the robot arm system are assembly, painting, welding, pick and place operation, and others. Besides, many industries employ robot arms for various jobs such as selecting and putting, painting, and material handling. However, one of the most challenging issues in completing these jobs is determining the target location of the robot arm's end-effector. There are two different methods for analyzing the robot arm's movement: forward and inverse kinematic analysis. Based on the visual servo algorithm, this study uses inverse kinematics to execute the pick and place operation. First, an object recognition algorithm is implemented to identify the object to be grasped. Then, an algorithm to avoid any obstacles is done. The study's findings show that good system performance has been obtained in all three algorithms: first, object recognition algorithm, second, obstacle avoidance algorithm, and lastly, visual servobased pick and place operation. Thus, it can be concluded that the robot arm's visual servo algorithm is suitable for pick-and-place applications.

Crop Recognition Method Based On End-effector

With the increasing global population, the demand for agriculture is also on the rise. The crucial stages of agricultural production, namely fruit identification and picking, play a vital role in enhancing product quality and minimizing losses. Traditional manual processing methods, although time-tested, are not only inefficient but also challenging to maintain consistency, making them inadequate to meet the large-scale requirements of modern agricultural production. Consequently, the integration of automation technology has become a necessity. For agricultural robot the machine vision system often need to work in two typical environments, the field environment and the orchard environment. Depending on the varying objectives of operation in diverse environments, crop robots require the ability to rapidly identify fruits within images featuring significant color disparities between crops and two-dimensional field backgrounds. Consequently, a visual servo control system is being investigated. A novel camera attitude search method that employs active visual servo technology to minimize occlusions during orchard search is proposed. The recognition function of the end-effector is exceedingly crucial. The precision of the end effector's identification capabilities directly influences the success rate of automated operations. This is particularly evident in fruit picking, sorting, and other tasks, where the diverse shapes, maturity levels, and colors of fruits present significant challenges to the robotic arm's end effector. The rapid advancement of deep learning technology, however, offers a novel solution for the recognition of fruits by the robotic arm's end effector. By emulating the human visual system, deep learning models can extract the feature representation of fruits from vast amounts of data, enabling accurate identification of fruits in various conditions.

3D-AMM: a 3D artificial moment method for path planning of manipulator in multiple obstacles scenario

PurposeIn response to the issue of traditional algorithms often falling into local minima or failing to find feasible solutions in manipulator path planning. The purpose of this paper is to propose a 3D artificial moment method (3D-AMM) for obstacle avoidance for the robotic arm's end-effector.Design/methodology/approachA new method for constructing temporary attractive points in 3D has been introduced using the vector triple product approach, which generates the attractive moments that attract the end-effector to move toward it. Second, distance weight factorization and spatial projection methods are introduced to improve the solution of repulsive moments in multiobstacle scenarios. Third, a novel motion vector-solving mechanism is proposed to provide nonzero velocity for the end-effector to solve the problem of limiting the solution of the motion vector to a fixed coordinate plane due to dimensionality constraints.FindingsA comparative analysis was conducted between the proposed algorithm and the existing methods, the improved artificial potential field method and the rapidly-random tree method under identical simulation conditions. The results indicate that the 3D-AMM method successfully plans paths with smoother trajectories and reduces the path length by 20.03% to 36.9%. Additionally, the experimental comparison outcomes affirm the feasibility and effectiveness of this method for obstacle avoidance in industrial scenarios.Originality/valueThis paper proposes a 3D-AMM algorithm for manipulator path planning in Cartesian space with multiple obstacles. This method effectively solves the problem of the artificial potential field method easily falling into local minimum points and the low path planning success rate of the rapidly-exploring random tree method.

Dual Performance Optimization of 6-DOF Robotic Arm Trajectories in Biomedical Applications

For the first time, dual-performance perfection technologies were used to kinematically operate sophisticated robots. In this study, the trajectory development of a robot arm is optimized using a dual-performance perfection technique. The proposed approach alters the robot arm's Kinematics by creating virtual points even if the robotic system is not redundant to make it kinematically suitable for biomedical applications. In the suggested method, an appropriate objective function is chosen to raise one or maybe more performance measures while lowering one or more kinematic characteristics of a robot arm. The robot arm's end effector is set in place at the crucial locations, and the dual performance precision algorithm changes the joints and virtual points due to the robot arm's self-motion. As a result, the ideal values for the virtual points are established, and the robot arm's design is changed. Accordingly, this method's ability to visualize modifications made to the processor's design during the optimization problem is one of its benefits. The active robotic arm is used as a case study in this article. The task is defined as choosing the best path based on the input target's position and direction and is used in X-ray robot systems. The outcomes demonstrate the viability of the suggested approach and can serve as a useful prototype for an intelligent X-ray robot.

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.

Bilateral Teleoperation with a Shared Design of Master and Slave Devices for Robotic Excavators in Agricultural Applications

The main objective of this study is to develop a shared design of master and slave devices for bilateral teleoperation mechanisms used for robotic excavators in agricultural applications. In robot teleoperation research, many potential applications within controlled and hazardous environments come to light. Robots, with their capacity for remote control by human operators through master devices, often employ the master-slave teleoperation approach. This strategy finds frequent use across manufacturing, construction, and agriculture industries. The master-slave system necessitates two interdependent components that collaboratively steer the robot in real time. However, challenges arise when manipulating the robot arm proves challenging due to structural differences between the master device (such as a joystick) and the slave device (the robot arm). A stable operational framework must be established for the robot to function optimally. This teleoperation system employs a master device to govern the actions of the slave device, a dynamic that heavily influences the operational complexity. Hence, the focal point of this study is to enhance the master-slave algorithm for teleoperation applications that rely on controlling robot arm movements. Despite the differing dimensions of the master and slave devices, they both share a common structure. The kinematic model bridging these components must be intelligible to ensure user-friendliness, facilitating effortless robot control. Calculating the robot arm's end effector movement and positioning involves employing the forward kinematics of the arm, determined through Denavit-Hartenberg parameters and transformation matrices. By mitigating communication delays between the master and slave devices using a technique centered around the robot arm's end effector position, the effectiveness of teleoperation can be significantly improved. Our designed robot arm attains 80% to 100% precision across joints. In summary, streamlining the robot arm's structure and minimizing delays offers a route to bolstering both stability and efficiency in robotic movement.

2D of Robotic Arm Based on Inverse Kinematics Using Arduino

Abstract: The advancements and quick developments in the technology has made it possible to create a platform for the invention of new as well as great things. One of the concept that is being used lately to improve the technology is the concept of robotics. This project focuses on the implementation of inverse kinematics for a 2-DOF (two degrees of freedom) robot arm using an Arduino microcontroller. The inverse kinematics equations are derived and programmed to calculate the joint angles required to position the robot arm's end effector in a desired location within its workspace. The Arduino board is used to interface with the robot arm's actuators and control the movement of the arm. The Arduino programming aspect of the project involves developing a control algorithm that accepts target coordinates for the end effector and computes the necessary joint angles using inverse kinematics equations. Servo motors are manipulated through the Arduino Servo library to achieve the calculated angles, enabling the arm to reach the desired positions accurately and efficiently. To enhance the functionality and safety of the 2-DOF robotic arm, the project includes features such as calibration routines, testing procedures, and safety measures to avoid collisions and servo load. The project aims to demonstrate the application of inverse kinematics in controlling robotic manipulators for precise positioning tasks

Higher Efficient Fruit Robot with Improved End Effectors

Under the situation that the technology level is improving recent year and the labor cost is increasing rapidly. In this paper, an autonomous harvesting robot with high efficiency is presented. The robot needs a fruit harvesting process with high obstacle avoidance efficiency for picking in complex and unstructured environments. In this research, the end-effector of the robotic arm picking process is optimized to reduce the number of times the fruit is crushed and to obtain the nearest moving trajectory to improve the picking efficiency. Therefore, the research topic of this paper is to optimize the picking method of the picking robot when performing picking operations. The following describes this paper's research methodology: first, the mechanical part of this harvesting robot is modeled, and then the most efficient way of the robot arm is found by analyzing the data of this model and combining it with the existing research. In this paper, it was found that changing the robotic arm's end-effector to a cylinder with a cutting blade would not only maximize the efficiency of the arm, but also ensure that the fruit would not be scratched. From this study, it was concluded that the end-effector can be customized to ensure efficient fruit picking according to the type of fruit and the approximate growth of the orchard fruit.

Adaptive chaos control of a humanoid robot arm: a fault-tolerant scheme

Abstract. Safety in human–robot physical interaction and cooperation is of paramount interest. In this work, a human–humanoid interaction and cooperation scenario is considered. The robot arm is controlled by a proportional derivative (PD) controller in combination with an inherently fault-tolerant sliding-mode controller. During normal operation, if any of the joints of the robot arm develops a fault, the robot arm end effector may go into chaotic and dangerous motion. If such a scenario occurs, it poses a serious danger to the human in the loop as well as the robot. In this paper, an adaptive chaos sliding-mode controller is proposed to recover the tracking of the end effector when a fault occurs in any of the actuators. This tracking restoration is very important to complete a safety-critical task. The proposed scheme may help in addressing some safety issues arising from a joint failure, allowing it to finish the task at hand and stop it from going into a dangerous situation. The scheme is tested in simulation on the four degrees of freedom (DOF) model of the Bristol Robotics Laboratory (BRL) robot arm. Simulation results show efficient tracking recovery after a joint actuator failure. The controller demonstrated good performance in terms of tracking and stability when dealing with different joint actuator failures.

Robotic Arm Gripper Using Force Sensor for Crop Picking Mechanism

A dynamic gripper with qualities that resemble the human hand as closely as possible is sought after in the field of robotics. The idea of a robotic arm has been used in various cutting-edge technology fields, including agriculture, to assist people or farmers in carrying out regular tasks, such as gathering fruit, etc. The robot arm's end effector is one of the essential parts of the robot that we can configure based on their tasks, such as a spraying adaptor for fertilization function or a gripper for the picking mechanism. Since fruits have a delicate and fragile surfaces, it is vital to have a gripper with a smooth contact surface that can apply the right amount of force to pick the fruits without causing any bruising that can degrade the crop's quality. Hence, this paper proposes a robotic arm gripper design for the crop-picking mechanism using a force sensor as the main component of the Arduino Uno embedded system. The reliability result for the chili obtained is around 95% showing that this design is promising for designing an adaptive robotic arm gripper.

A Tandem Robotic Arm Inverse Kinematic Solution Based on an Improved Particle Swarm Algorithm.

The analysis of robot inverse kinematic solutions is the basis of robot control and path planning, and is of great importance for research. Due to the limitations of the analytical and geometric methods, intelligent algorithms are more advantageous because they can obtain approximate solutions directly from the robot’s positive kinematic equations, saving a large number of computational steps. Particle Swarm Algorithm (PSO), as one of the intelligent algorithms, is widely used due to its simple principle and excellent performance. In this paper, we propose an improved particle swarm algorithm for robot inverse kinematics solving. Since the setting of weights affects the global and local search ability of the algorithm, this paper proposes an adaptive weight adjustment strategy for improving the search ability. Considering the running time of the algorithm, this paper proposes a condition setting based on the limit joints, and introduces the position coefficient k in the velocity factor. Meanwhile, an exponential product form modeling method (POE) based on spinor theory is chosen. Compared with the traditional DH modeling method, the spinor approach describes the motion of a rigid body as a whole and avoids the singularities that arise when described by a local coordinate system. In order to illustrate the advantages of the algorithm in terms of accuracy, time, convergence and adaptability, three experiments were conducted with a general six-degree-of-freedom industrial robotic arm, a PUMA560 robotic arm and a seven-degree-of-freedom robotic arm as the research objects. In all three experiments, the parameters of the robot arm, the range of joint angles, and the initial attitude and position of the end-effector of the robot arm are given, and the attitude and position of the impact point of the end-effector are set to verify whether the joint angles found by the algorithm can reach the specified positions. In Experiments 2 and 3, the algorithm proposed in this paper is compared with the traditional particle swarm algorithm (PSO) and quantum particle swarm algorithm (QPSO) in terms of position and direction solving accuracy, operation time, and algorithm convergence. The results show that compared with the other two algorithms, the algorithm proposed in this paper can ensure higher position accuracy and orientation accuracy of the robotic arm end-effector. the position error of the algorithm proposed in this paper is 0 and the maximum orientation error is 1.29 × 10–8. while the minimum position error of the other two algorithms is −1.64 × 10–5 and the minimum orientation error is −4.03 × 10–6. In terms of operation time, the proposed algorithm in this paper has shorter operation time compared with the other two algorithms. In the last two experiments, the computing time of the proposed algorithm is 0.31851 and 0.30004s respectively, while the shortest computing time of the other two algorithms is 0.33359 and 0.30521s respectively. In terms of algorithm convergence, the proposed algorithm can achieve faster and more stable convergence than the other two algorithms. After changing the experimental subjects, the proposed algorithm still maintains its advantages in terms of accuracy, time and convergence, which indicates that the proposed algorithm is more applicable and has certain potential in solving the multi-arm inverse kinematics solution. This paper provides a new way of thinking for solving the multi-arm inverse kinematics solution problem.

A positioning error compensation method for multiple degrees of freedom robot arm based on the measured and target position error

A novel positioning error compensation method (PECM) based on the measured and target position error for multiple degrees of freedom (DOF) robot arm control is proposed, which is used to improve positioning accuracy of multiple-DOF robot arm end-effector in accurate positioning applications such as in the medical and mechanical fields. Based on the idea of PID to increase adaptiveness and robustness of the method, a positioning compensation model between the measured and target position error tracked by an optical tracking system and compensated joint angle is derived with inverse kinematic model. Based on error analysis of the compensation model regarding geometry errors, the proportional joint angle compensated coefficient deduced from Jaccobian matrix of the error is proposed and identified with position error data. Calibration experiments for position conversion matrix and positioning accuracy verification experiments are conducted consisting of an optical tracking system and a robot arm. The results of positioning accuracy verification experiments show that the average resultant positioning error in three directions reduces from 1.89 mm (before compensation, model based on Denavit-Hartenberg (DH)), 0.39 mm (model based on modified Denavit-Hartenberg (MDH) with Levenberg-Marquardt (LM)) to 0.34 mm (decreasing 82%, 15%), which demonstrates the efficiency and robustness of the method.

Finger/Chin Joystick Control for Robotic Arms and Power Wheelchair Systems

<h3>Research Objectives</h3> To provide a reliable and easy to Joystick controlled transportation/manipulation system for individuals with restricted mobility for their daily tasks. <h3>Design</h3> Experimental study. <h3>Setting</h3> In UWM BioRobotics Lab. <h3>Participants</h3> Healthy and young participants. <h3>Interventions</h3> Collaborative Robotic Arm for Activities of Daily Living assistance (picking objects from a desk, the floor, opening doors, drawers and eating), finger/Chin Joystick Control. <h3>Main Outcome Measures</h3> * Control robotics arm with finger and chin while keeping control of the wheelchair's mobility. * A lightweight software capable of controlling a robotic arm with generic/commercial joysticks. * Intuitive and easy to learn operability of the robotic arm with its multiple control modes. <h3>Results</h3> The system is composed by a power wheelchair (in this case a Permobil M3 Corpus), a robotic arm (a 6 Degree of Freedom arm with its control box) and the two user joysticks (finger and chin). Some circuitry was developed in order to communicate with the wheelchair electrical system. The experiments were performed by healthy personal in order to measure the operability and ease to use of this controller. The experiment's mean time as well as its difficulty seen by the participants were some of the variables to compare. A 3D trajectory of the robot arm end effector was recorded for the 4 different Activities in the Daily Living using the two different control devices. Each experiment had a fixed position for the wheelchair and the same initial position for the robotic arm. <h3>Conclusions</h3> The finger/chin joystick control is meant for individuals with restricted mobility, to allow them to perform their activities of daily living that were previously impossible to. This method will allow the to integrate a robotic arm in their power wheelchair system and expand its capabilities. <h3>Author(s) Disclosures</h3> No conflict.

Computed Torque Control Method for Two-Axis Planar Serial Robotic Arm

The heat generated in reactor core is extracted using the sodium water heat exchanger system in fast breeder reactor. In the heat exchanger system there are 8 steam generators. Steam generator uses sodium and water to generate steam. Sodium–water reaction is exothermic in nature, so SG tubes need inspection to check healthiness of the tube. Due to space constraints, in-service inspection of SG needs remote-controlled robotic arm to locate SG tubes. The tube sheet is planar, so revolute joint two-link robotic arm is adapted. The movement of two-axis robotic arm needs control on position as well as velocity. The dynamic equation of two-axis robotic arm is coupled in nature which makes the control of end effector very difficult. The un-modeled phenomena, as that of friction and errors in mass distribution, will drastically affect the tracking of the end effector in the desired path. The Coriolis Effect is also accounted in the model. To precisely control the robotic arm end effector, the computed torque control technique is proposed and used in this paper.

Comparative study of the VINCI Robot's arm end effector matrix using Python and MATLAB

The transformation matrix based on D-H parameters has been utilized to find the end effector of serial manipulator viz., surgical Robot, single-finger type, nano manipulator, etc. For object manipulation at microscale and texture identification using tactile finger at end effector, it is essential for nano manipulator and tactile finger to be more precise and accurate. The accuracy and precision of these manipulators depend on the orientation and position computed by the used software platform. The present study compares the end effector matrix of the VINCI robotic arm with D-H parameters using MAT LAB and PYTHON. The transformation matrix of order 4 × 4 described the end effectors position and orientation concerning to fixed base. The Forward Kinematics of the Vinci Robot 4 DOF (degree of freedom) is calculated using MAT LAB and Python software compared with the End effector matrix. The comparative study of the end effector matrix shows that Python is more accurate and efficient in orientation and position.

A YOLOv2 Convolutional Neural Network-Based Human–Machine Interface for the Control of Assistive Robotic Manipulators

During the last years, the mobility of people with upper limb disabilities and constrained on power wheelchairs is empowered by robotic arms. Nowadays, even though modern manipulators offer a high number of functionalities, some users cannot exploit all those potentialities due to their reduced manual skills, even if capable of driving the wheelchair by means of proper Human–Machine Interface (HMI). Owing to that, this work proposes a low-cost manipulator realizing only simple tasks and controllable by three different graphical HMI. The latter are empowered using a You Only Look Once (YOLO) v2 Convolutional Neural Network that analyzes the video stream generated by a camera placed on the robotic arm end-effector and recognizes the objects with which the user can interact. Such objects are shown to the user in the HMI surrounded by a bounding box. When the user selects one of the recognized objects, the target position information is exploited by an automatic close-feedback algorithm which leads the manipulator to automatically perform the desired task. A test procedure showed that the accuracy in reaching the desired target is 78%. The produced HMIs were appreciated by different user categories, obtaining a mean score of 8.13/10.

Chaos Stabilization and Tracking Recovery of a Faulty Humanoid Robot Arm in a Cooperative Scenario

Synchronised motion is an important requirement for two cooperating humanoid robot arms. In this work a cooperative scenario is considered where two humanoid robot arms (using 4DOF each, namely Shoulder Flexion Joint, Shoulder abduction Joint, Humeral rotation joint and Elbow Flexion Joint) motion are synchronized. The master robot arm is controlled by a sliding mode controller and the slave robot arm is synchronized using a basic PD plus adaptive control, employing the position and velocity errors between the master and the slave. During the operation, if a joint of the slave robot arm saturates or malfunctions (for instance, Elbow flexion joint does not respond or free swinging), consequently, slave robot arm will go into chaos (i.e., chaotic motion of the end effector). In this case, a chaos controller kicks in to recover and re-synchronize the motion of the slave robot arm end effector. This re-synchronization is extremely important to complete the task in hand to address any safety issues arising from any joint malfunction of the slave robot. Effectiveness of the scheme is tested in simulation using Bristol Robotics Laboratory Humanoid BERT II arms.

Onboard centralized frame tree database for intelligent space operations of the Mars Science Laboratory Rover.

Planetary surface science operations performed by robotic space systems frequently require pointing cameras at various objects and moving a robotic arm end effector tool toward specific targets. Earlier NASA Mars Exploration Rovers did not have the ability to compute actual coordinates for given object coordinate frame names and had to be provided with explicit coordinates. Since it sometimes takes hours to more than a day to get final approval of certain calculated coordinates for command uplink via the Earth-based mission operations procedures, a highly desired enhancement for future rovers was to have the onboard automated capability to compute the coordinates for a given frame name. The Mars Science Laboratory (MSL) rover mission is the first to have a centralized coordinate transform database to maintain the knowledge of spatial relations. This onboard intelligence significantly simplifies communication and control between Earth-based human mission operators and the robotic rover on Mars by supporting higher level abstraction of commands using object and target names instead of coordinates. More specifically, the spatial relations of many object frames are represented hierarchically in a tree data structure, called the frame tree. Individual frame transforms are populated by their respective modules that have specific knowledge of the frames. Through this onboard centralized frame tree database, client modules can query transforms between any two frames and support spacecraft commands that use any frames maintained in the frame tree. Various operational examples in the MSL mission that have greatly benefitted from this onboard centralized frame tree database are presented.

3P1-R01 空気圧アクチュエータを用いたロボットハンドの関節角度制御(ロボットハンドの機構と把持戦略(1))

Currently, reduction of the population beginning in Japan, declining labor force is threatened. Factory automation, and the like as a solution to this problem in the industrial field. Material handling technology is one prime example. However, work performance due to the current robot can not be said to be too high. So, we made a study of the robot arm end effector as a highly versatile, with a robot hand of five fingers in this study. Nonlinearity and hysteresis are present in the pneumatic artificial manipulator is a driving source, it is difficult to control. In the middle finger joint angles of the hand unit, we have verified the effectiveness of the joint angle controller.

Uniaxial Wireless Tissue Palpation Device for Minimally Invasive Surgery

Nowadays surgery tends to be performed with minimally invasive techniques that result in less post-operative pain, recovery time and smaller incisions. However, unlike open surgery, during minimally invasive surgery (MIS) the surgeon has few chances to rely on tactile and kinesthetic feedback [1]. Tissue palpation aids in preventing traumas or in leveraging tactile information to identify tumors, vessels and organic structures buried underneath the tissue surface. Therefore, in the last two decades, research on palpation devices strived to restore tactile and kinesthetic sensations in MIS. This was pursued by performing tissue palpation with different techniques, such as indenting [2], grasping [3] or rolling [1]. Despite this research effort, a translation into clinical practice is still far to come. Even further, surgeons are resistant to the option of devoting a surgical port to a palpation device, because of the available ports are needed for the MIS instruments. As an alternative to this approach, intraoperative ultrasonography devices (IOUS) may be used to detect buried structures [4]. Also this technology, however, requires a dedicated surgical port during the entire procedure.