Design Of Robotic Arm Research Articles

Design and development of machine vision robotic arm for vegetable crops in hydroponics

Modern agricultural machinery such as harvesting robotic arms are necessary to optimize the semi-automated agricultural processes to meet the ever-growing food needs of the population of the world. Production of low cost and highly efficient robotic arms are needed to meet the needs of the small-scale growers of underdeveloped countries. In this regard, mechanical design, sensor placement, and object identification are essential to optimize the performance of agricultural robots. This research is conducted to design a fully automated robotic arm for fruit picking in hydroponics system and research farm using machine vision to help the smallholders. For this purpose, a robotic arm with 1.3 m in height is designed using aluminum (18-gauge) and mild steel (MS-16) as fabrication material for the mechanical structure. The prototype design is tested for stress estimation at various payloads using SolidWorks simulations. The proposed robotic arm is based on a four degrees of freedom (4-DoF) design with the gripper having an opening range of 5.5 to 12 cm depending upon the task to handle various objects. The robotic arm is installed on an expandable vertical mobile platform that enables an expanded operational workspace with lower energy consumption. The total weight of the robotic arm is 60 kgs housing a payload capacity ranging between 8 and 10 kgs in accordance with industry-standard load-bearing specifications. The inverse kinematic algorithm using DH-table is computed with an accuracy of up to 95 % and target height of gripper is cross checked by mounting the ultrasonic sensor at the base of robotic arm. The YOLOv8 algorithm is used for object detection using the depth sense camera having angle range of 0.3 m to 3 m with the precision of up to 96 %. The time needed for recognition of fruits and pitching was about 15 s, with a success rate of up to 90 %. This research produces a low-cost and efficient solution for stallholders by developing a fully automated robotic arm for fruit picking. It optimizes agricultural productivity through improved mechanical design, sensor accuracy, and object detection which reduces labor costs by increasing efficiency of semi-automated farming systems. Further research is required to optimize the overall weight of the system and automation of the movement of robotic arm system between the consecutive rows to build a fully autonomous fruit picking operation in hydroponics.

Design and Development of a 5-DOF SCARA Robot Arm for Robotics Education in a STEM Laboratory

The development of a 5-degree-of-freedom (DOF) SCARA robot arm was successfully achieved for educational use within the CSL Laboratory at the School of Applied STEM, Universitas Prasetiya Mulya. The design utilizes cost-effective, locally sourced materials and an open-source control system based on Processing Java and Arduino C. These features make the SCARA robot arm an accessible tool for students to learn robotics, particularly in the areas of kinematics, control, and programming. Extensive testing of the robot’s inverse kinematics algorithm showed promising results, with average error rates of 1.20% for the Inner Arm, 4.21% for the Outer Arm, and 3.39% for the Z-axis. These low error rates highlight the robot’s precision in movement. This research not only met its objective of creating an accessible platform for teaching robotics but also demonstrated potential for future development in robotics education and industrial applications.

Design and Simulation of an Innovative Modular Four-Bar Linkage Robotic Arm: Analysis and Applications

In response to the issues of traditional manipulators, such as difficulty in controlling the terminal posture during motion, low control precision, and complex structure, a modular mechanical arm based on a parallel four-bar terminal posture maintenance mechanism has been designed to meet the special requirements of terminal posture maintenance. By analyzing the motion mechanism of the manipulator, the shape space of the manipulator, the terminal position space, and the relationships of forward and inverse kinematics have been derived. A simulation model of the linkage manipulator was established in the Robotic Toolbook for Matlab environment, and structural simulation analysis and kinematic equation verification were conducted. The end positioning and attitude control of different manipulators are simulated by Matlab programming. The working space of the manipulators is calculated by Monte Carlo method, and compared with that of traditional planar manipulators. The results show the validity of the kinematics equation and the rationality of the end positioning control scheme of the linkage manipulator. Finally, the experiment verifies that the attitude retention rate of the modular decoupling manipulator is 97.78% under high load, which verifies the reliability of this scheme. In addition, the manipulator can simplify the complexity of the mechanical structure and complete the control requirements of the terminal attitude under the premise of increasing the working space as much as possible, which lays a foundation for the design and optimization of the manipulator in the field of modular terminal attitude.

Design and motion analysis of soft robotic arm with pneumatic-network structure

Design and motion analysis of soft robotic arm with pneumatic-network structure

RANCANG BANGUN TRAINABLE ROBOT ARM BERBASIS ARDUINO MEGA 2560 SEBAGAI MEDIA PRAKTIKUM DI LABORATORIUM TEKNIK ELEKTRO UNIVERSITAS PEMBANGUNAN PANCABUDI MEDAN

The design of the Trainable Robot Arm is carried out as a learning medium in the lab. Electrical Engineering University of Development Pancabudi Medan. Trainable Robot Arm is a robotic arm designed to facilitate the process of robot applications in carrying out object transfer tasks without the need to do complex programming every time you want to change the robot's movements. The design of this arm robot is divided into 3 parts, the first is the design and manufacture of robot mechanics, the second is the design and manufacture of robot control/electricity and the third is the manufacture of robot software/programs. The mechanical design of the robot begins with making a 3D design of the robot frame utilizing the non-commercial version of the Fusion360 CAD software, then the 3D design is printed using a 3D Printing machine with PETG (Polyethylene Terephthalate) plastic material. The robot arm is designed to have a 5-DOF (Deegre of Freedom) system, namely Base, Shoulder, Elbow, Wrist and Gripper. As a drive, 5 servo motors with torque are used each, 25 kg/cm for Base and Shoulder, 11kg/cm for Elbow and Wrist, and 1.8 kg/cm for Gripper. From the test results, the Trainable robot arm successfully stores and repeats movements that have been trained to move objects with a mass of 100 grams at a position of 23cm from the axis of the robot arm to the x-axis to a position of 20cm from the axis of the robot to the y-axis as many as 8 repetitions without failure.

Automatic Tea Ceremony Teapot Robotic Arm Design Based on TRIZ Principle

With the accelerated pace of modern society, there is a contradiction between the tedious steps of traditional tea ceremony and the convenient lifestyle. In order to solve this problem, this study applies the TRIZ theory to optimize the design of the fully automatic tea ceremony teapot robot arm. Through the "nine-screen method", the traditional tea-making process was comprehensively analyzed, the key steps were identified, and the cultural significance and technical requirements of each step were discussed in depth. Using the "technical contradiction matrix" and "physical contradiction" analysis, the potential contradictions in the tea-making process were revealed, and the "physical field model" was applied to construct the problem model and explore the possible solutions. The problem model was constructed by applying the "Physical Field Model", and possible solutions were explored. The study proposes a fully automated tea art teapot robotic arm design program that integrates several key technology modules such as heating and temperature control, plane movement, lid operation, and pouring and dispensing of tea. The program ensures the quality of tea soup and the experience of traditional tea ceremonies through the well-designed robotic arm structure and improves the efficiency of tea brewing at the same time. The structural safety of the design scheme is verified by stress analysis of the connecting plate of the robotic arm and the connecting plate of the teapot base. Finally, the feasibility and effectiveness of the proposed scheme are verified through kinematic analysis, prototype testing, and user experience evaluation. This study is of great practical significance for the modernization and transformation of the traditional tea ceremony and also provides a reference for the automation of other traditional crafts. With the continuous progress of technology, we expect more innovative products combining traditional culture and modern technology to appear in the future so that traditional art can be revitalized in modern society.

Design and Nonlinear Modeling of a Modular Cable-Driven Soft Robotic Arm

Design and Nonlinear Modeling of a Modular Cable-Driven Soft Robotic Arm

Structural Optimization of 4-DOF Agricultural Robot Arm

The shortage of human labor is increasing; thus, more agricultural machinery and equipment are expected to enter the agricultural sector. One of the agricultural machinery widely studied nowadays involves robot arms. Therefore, developing robot arms is a hot issue in this field. The ideal structure of the robot arm with optimal length is currently gaining popularity and being used in many sectors, such as manufacturing and agriculture. This is closely related to the dynamic structure of agricultural areas. Therefore, this study uses the forward kinematic modeling method to design an optimal robot arm to achieve a specific coordinate in a dynamic environment. The robot in this study arm mimics the boom and arm installed on a tractor. The forward kinematic problem in this study is defined using the Denavit-Hartenberg (DH) convention method. The DH convention is commonly used to solve kinematic analysis problems of a robot arm. Simulation of kinematic modeling is performed using MATLAB software. This study studies various optimization algorithms to compare the performance of algorithms that can achieve the optimal length with minimum errors. The comparison between artificial bee colony (ABC) and particle swarm optimization (PSO) is studied. At the end of the study, the best algorithm was selected for the robot arm design with a four-degree-of-freedom (4-DOF). The best algorithm, i.e., the PSO algorithm, is evaluated by calculating mean square error (MSE of 0.00108527), root mean square error (RMSE of 0.01678), mean absolute error (MAE of 0.004286081), and end-effector position error (error of 0.080557045), where the best algorithm has the lowest value of error.

Multimodal radiotherapy dose prediction using a multi-task deep learning model.

In radiation therapy (RT), accelerated partial breast irradiation (APBI) has emerged as an increasingly preferred treatment modality over conventional whole breast irradiation due to its targeted dose delivery and shorter course of treatment. APBI can be delivered through various modalities including Cobalt-60-based systems and linear accelerators with C-arm, O-ring, or robotic arm design. Each modality possesses distinct features, such as beam energy or the degrees of freedom in treatment planning, which influence their respective dose distributions. These modality-specific considerations emphasize the need for a quantitative approach in determining the optimal dose delivery modality on a patient-specific basis. However, manually generating treatment plans for each modality across every patient is time-consuming and clinically impractical. We aim to develop an efficient and personalized approach for determining the optimal RT modality for APBI by training predictive models using two different deep learning-based convolutional neural networks. The baseline network performs a single-task (ST), predicting dose for a single modality. Our proposed multi-task (MT) network, which is capable of leveraging shared information among different tasks, can concurrently predict dose distributions for various RT modalities. Utilizing patient-specific input data, such as a patient's computed tomography (CT) scan and treatment protocol dosimetric goals, the MT model predicts patient-specific dose distributions across all trained modalities. These dose distributions provide patients and clinicians quantitative insights, facilitating informed and personalized modality comparison prior to treatment planning. The dataset, comprising 28 APBI patients and their 92 treatment plans, was partitioned into training, validation, and test subsets. Eight patients were dedicated to the test subset, leaving 68 treatment plans across 20 patients to divide between the training and validation subsets. ST models were trained for each modality, and one MT model was trained to predict doses for all modalities simultaneously. Model performance was evaluated across the test dataset in terms of Mean Absolute Percent Error (MAPE). We conducted statistical analysis of model performance using the two-tailed Wilcoxon signed-rank test. Training times for five ST models ranged from 255 to 430min per modality, totaling 1925min, while the MT model required 2384min. MT model prediction required an average of 1.82s per patient, compared to ST model predictions at 0.93s per modality. The MT model yielded MAPE of 1.1033±0.3627% as opposed to the collective MAPE of 1.2386±0.3872% from ST models, and the differences were statistically significant (p=0.0003, 95% confidence interval=[-0.0865, -0.0712]). Our study highlights the potential benefits of a MT learning framework in predicting RT dose distributions across various modalities without notable compromises. This MT architecture approach offers several advantages, such as flexibility, scalability, and streamlined model management, making it an appealing solution for clinical deployment. With such a MT model, patients can make more informed treatment decisions, physicians gain more quantitative insight for pre-treatment decision-making, and clinics can better optimize resource allocation. With our proposed goal array and MT framework, we aim to expand this work to a site-agnostic dose prediction model, enhancing its generalizability and applicability.

Design and Fabrication of 3D-Printed Robotic Arm by Using Stepper Motor

Abstract: The Main technology of this proposed work was to design and fabrication of pick and place robotic arm by 3d-printing technology. The robot arm will be designed with four degree of freedom and programmed to accomplish accurately simple light material pick and place task to assist in the production line in any industry. ARDUNO an open-source computer hardware and software is applied to control robot arm by driving four servo motors to be capable to modify the position wireless control was done by using a Smartphone with android operating system through a Bluetooth module. The robotic arm Working and its performance in execution of pick and place task should be analyzed

A Sinh-Cosh-Enhanced DBO Algorithm Applied to Global Optimization Problems.

The Dung beetle optimization (DBO) algorithm, devised by Jiankai Xue in 2022, is known for its strong optimization capabilities and fast convergence. However, it does have certain limitations, including insufficiently random population initialization, slow search speed, and inadequate global search capabilities. Drawing inspiration from the mathematical properties of the Sinh and Cosh functions, we proposed a new metaheuristic algorithm, Sinh-Cosh Dung Beetle Optimization (SCDBO). By leveraging the Sinh and Cosh functions to disrupt the initial distribution of DBO and balance the development of rollerball dung beetles, SCDBO enhances the search efficiency and global exploration capabilities of DBO through nonlinear enhancements. These improvements collectively enhance the performance of the dung beetle optimization algorithm, making it more adept at solving complex real-world problems. To evaluate the performance of the SCDBO algorithm, we compared it with seven typical algorithms using the CEC2017 test functions. Additionally, by successfully applying it to three engineering problems, robot arm design, pressure vessel problem, and unmanned aerial vehicle (UAV) path planning, we further demonstrate the superiority of the SCDBO algorithm.

Real-Time Telerobotic Manipulator Control Using Hand Gestures

Control of Objects from a remote distance became an important factor for mankind about decades ago. Since then there has been a tremendous amount of improvements in the field of remote control. Once the “Internet of Things(IoT)” had been introduced, remote control technology across various applications has also opted for this method of data transmission from device to device over the internet. Through this work, a new way of controlling a robotic arm that can mimic/repeat human hand gestures and operate in a remote location through the use of IoT technology is proposed. The robotic arm design involves generative designing for weight reduction over a five end-effector model for cost and weight reduction purposes, also for the cause of hand gesture recognition a Neural Network has been trained and implemented behind an application that has been completely programmed in python. As compared to traditional methods of controlling a robotic arm the proposed method provides better cost efficiency, data transmission, data collection, and accessibility due to the abundant availability of computers, and adaptability towards the growing technology.

Cost-effective Robotic Arm Simulation and System Verification

In recent years, the utilization of virtual environments in industry 4.0 has witnessed significant growth, particularly in the design, implementation, and management of robotic systems. This paper addresses the need for enhanced control in robotic arms by presenting the design and implementation of a 5DoF robotic arm transformed into a digital platform through specialized software. The methods employed involve detailed direct and inverse kinematic modeling to replicate the physical arm in a digital environment. Our measurements indicate an impressive accuracy ranging from 97% to 100% in the movements of the digital model, closely mirroring its physical counterpart. This research not only contributes to the development of simulation systems but also holds promise for the broader adoption of digital twins. The paper discusses the background, outlines the methodology, highlights key findings, and concludes with the potential future impact of this work on the advancement of robotic systems and simulation technologies.

Design of robotic arm for the porcelain bushing in substation

With the development and the application popularization of artificial intelligence robot technology and 5G technology, a robotic arm is designed and developed for rinsing porcelain bushing in high voltage substation in this paper. Firstly, the components and implementation of robotic arm are presented, subsequently, a circular cleaning structure with a 120-degree split is proposed to rinse the porcelain bushing. Secondly, a two-stage simple and effective method to realize automatic orientation is proposed utilizing photoelectric switches. Moreover, a prototype of robotic arm with control system is developed based on the regime switching function, and the result of edge computing is transmitted by 5G technology. Finally, feasibility and effectiveness of the robotic arm are verified in the Nanjing power grid. The case study manifests that the robotic arm developed by the proposed method in the paper can achieve efficient rinsing and all the corresponding information can be transmitted preciously. The proposed method lays a foundation for wide application of cleaning robot in high voltage substation.

Design, Analysis and Fabrication of Pick and Place Robotic Arm with Multipurpose

Abstract: This project is to design, develop and fabricate a "pick and place robotic arm" using Raspberry pi controller. It will pick and place an object from source to destination safely. This robot has a gripping technology that is used to lift, hold, grasp, and replace materials from one place to another. This robotic has revolute joints that allow the angular movement of the adjacent joint. The objective of this project is to design and build a more compact, usable and cheaper pick and place robotic arm for educational purpose. It uses Raspberry pi as the control system to control all the activities. Inputs to the Robotic arm are predefined. In the project we are applying this concept to the design of pick and place robotics system using SolidWorks Soft motion software. The software is used to design a Cartesian robot and an articulated industrial robotic arm with different grippers. The robot was designed using the SolidWorks’ 3D CAD software to shorten the robot development time, and improve the speed and quality of the robot design.

Design of a Wheelchair-Mounted Robotic Arm for Feeding Assistance of Upper-Limb Impaired Patients

This paper delineates the design and realization of a Wheelchair-Mounted Robotic Arm (WMRA), envisioned as an autonomous assistance apparatus for individuals encountering motor difficulties and/or upper limb paralysis. The proposed design solution is based on employing a 3D printing process coupled with optimization design techniques to achieve a cost-oriented and user-friendly solution. The proposed design is based on utilizing commercial Arduino control hardware. The proposed device has been named Pick&Eat. The proposed device embodies reliability, functionality, and cost-effectiveness, and features a modular structure housing a 4-degrees-of-freedom robotic arm with a fixing frame that can be attached to commercial wheelchairs. The arm is integrated with an interchangeable end-effector facilitating the use of various tools such as spoons or forks tailored to different food types. Electrical and sensor components were meticulously designed, incorporating sensors to ensure user safety throughout operations. Smooth and secure operations are achieved through a sequential procedure that is depicted in a specific flowchart. Experimental tests have been carried out to demonstrate the engineering feasibility and effectiveness of the proposed design solution as an innovative assistive solution for individuals grappling with upper limb impairment. Its capacity to aid patients during the eating process holds promise for enhancing their quality of life, particularly among the elderly and those with disabilities.

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.

Development and implementation of a wireless-controlled robotic arm for lifting applications with 6 DOF

This paper is centered on the design and construction of a Bluetooth-controlled robotic arm with 6 degrees of freedom. It is capable of manipulating given objects as well as lifting and conveying a payload from one point to another. Any smartphone that possesses an Android operating system can be used for remote operations. This offers a background look at robotic arms, from invention to current trend as well as simplification of design to make it more accessible to robotics enthusiasts. The design process for the robotic arm is chronicled in this paper, from the working principle to the development of the kinematic equations, as well as CAD modeling and component selection. Tests are also conducted to ascertain the robot’s strength and range of capabilities. The availability of this robotic arm would serve as an indispensable learning tool for experimenting with robotics in training institutions.

A Dynamic Modeling Method for Soft Pneumatic Robotic Arms Considering Both Geometric Nonlinearity and Visco-Hyperelasticity

This work proposes a new dynamic modeling approach that integrates the principle of virtual power and a spring–damper–fluid equivalent method. It is able to simultaneously consider the geometric and material nonlinearity including hyperelasticity and viscoelasticity of the soft robotic arm. Meanwhile, the nonuniform deformation of the soft arm wall can be introduced into the model based on the equivalent model. A general prototype of soft robotic arms is fabricated and validation experiments of three pneumatic actuation modes are carried out. A maximum position error of 3.64[Formula: see text]mm at the end of the soft arm is obtained with an eight-segment theoretical model for the 280[Formula: see text]mm long and 30[Formula: see text]mm thick prototype in an approximate step actuation test with a maximum pneumatic pressure of 11.5[Formula: see text]kPa. The comparisons between the theoretical prediction and experimental results demonstrate a high accuracy of the proposed modeling method. Besides, simulations of dynamic motions under in-plane and out-of-plane actuation are carried out respectively, illustrating that the proposed method has the ability to describe a variety of actuation forms. The proposed dynamic modeling method provides a new way for modeling the soft robotic arms and has guiding significance for the design and control of soft robotic arms.

Finite element analysis and optimal design of robotic arm

With the rapid development of modern industry and Robotics, industrial robots are widely used in manufacturing. However, because of the high price of industrial robot systems on the market, industrial robots are limited to the production of small and medium-sized enterprises. Against this background, this paper fully investigates the development process and research status of industrial manipulators at home and abroad, and designs a six-degree-of-freedom economic industrial manipulator. ANSYS Workbench software is used to analyze the statics of the arm and the whole machine, and the equivalent stress cloud map and the displacement and deformation cloud chart are obtained. The static strength and stiffness of the large arm and the whole machine are analyzed, and the reliability of the structure is verified. Then adopting the optimization module in the software, the multi-objective optimization design of the large arm is carried out. The size of the structure is reduced and the quality is reduced by 14.7% in the case that the large arm meets the requirements of the allowable stress and the maximum displacement. The target of the optimization design is realized.