Industrial Robot Applications Research Articles

Automation and robotization of solid mineral mining

Improvement in competitiveness of mining clusters is inextricably linked with enhancement of labor safety and efficiency. Meeting these objectives is possible through wider implementation of robotic systems both at the stages of mining and transportation of minerals. The paper analyzes the current state, prospects and a general trend of development of robotic mining equipment. The advanced types of foreign and Russian automated equipment, and also the basic concepts and programs of robotization are considered. To date the areas of application of robotics in the mining industry include automated batching, rock excavation and transportation, mapping and geodesy, drilling and explosives processing. The introduction of robots in mining places special demands on their reliability and quality, and raises numerous problems and unresolved issues that both academia and industry must jointly identify and address. The widespread use of robotic technology in surface and underground mining can lead to significant changes in the design of quarries and mines, as well as in the safety regulations, and contribute to the development of new types of mining machinery and equipment, which will provide a significant increase in mining efficiency.

Food Serving Robot for Contactless Experience

As the world is emerging towards new trends and technologies; there is a need to invent something that is more attractive and useful for the citizens. This research work highlights a very young area of application and provides a comprehensive overview of the application of robotics in the food industry. In this new technological age, all jobs depend on a technology called automation. New research works are developed in the market instead of human workers being the fashion and new passion today. In this context, we develop the concept of the food serving robots (FSR) in this work. It required Arduino board and the Arduino IDE to build. In this research work the board is predefined by using color sensors and the obstacle sensor to identify the tables. This Application can be used in any hotel and restaurant, regular cycles. The use of robots in the food management system is very trendy. Internet of Things mechanisms (IoTM) are widely used to avoid human manual work. It also reduces the number of employees in a workplace. Once the structure is created, it works according to the user's instructions. Here in this Application we will create this robot for food delivery in hotels. In this paper, we consider two tables to show the operation of the robo and the so-called food delivery robot. In this robo build it required components like Arduino board, gear motor, motor controller, IR obstacle sensor, battery (6 volt), and jumper wires.

Overview of the KUKA robot language-based intelligent algorithms on industrial robots for multifaced medical and engineering applications

Industrial robots have been in use for about fifty years. Typical applications of industrial robots include biomedical, painting, palletizing, welding, assembly, and material handling. As healthcare robotic systems for diagnostics, surgical treatments, or rehabilitative services: Robotic technologies seem to be very well with a broad array of applications in automation medical advancements. Apart from medical, an algorithm is designed to play electronic musical keyboards with the help of an industrial robot. The algorithm is implemented on the KUKA KR-16 industrial robot. The robot plays an electronic musical keyboard according to the keyboard notes of the desired song. The algorithm is designed to make the input of musical notes simple and easy. The design algorithm is further developed with KRL (KUKA Robot Language). The proposed algorithm results show that the KUKA KR-16 can play the specified notes.

Calibration for a robotic drilling system with secondary encoders based on a novel enhanced rigid-flexible coupling model

PurposeThis paper aims to propose a novel model and calibration method to improve the absolute positioning accuracy of a robotic drilling system with secondary encoders and additional axis.Design/methodology/approachThe enhanced rigid-flexible coupling model is developed by considering both kinematic parameters and link flexibility. The kinematic errors of the robot and the additional axis are considered with a model containing 27 parameters. The elastic deformation errors of the robot under self-weight of links and end-effector are estimated with a flexible link model. For calibration, an effective comprehensive calibration method is developed by further considering the coordinate systems parameters of the drilling system and using a two-step process constrained Levenberg–Marquardt identification method.FindingsExperiments are performed on the robotic drilling system that contains a KUKA KR500 R2830 industrial robot and an additional lifting axis with a laser tracker. The results show that the maximum error and mean error are reduced to 0.311 and 0.136 mm, respectively, which verify the effectiveness of the model and the calibration method.Originality/valueA novel enhanced rigid-flexible coupling model and a practical comprehensive calibration method are proposed and verified. The experiments results indicate that the absolute positioning accuracy of the system in a large workspace is greatly improved, which is conducive to the application of industrial robots in the field of aerospace assembly.

Condition-Based Monitoring on High-Precision Gearbox for Robotic Applications

This work presents a theoretical and experimental study regarding defect detection in a robotic gearbox using vibration signals in both cyclostationary and noncyclostationary conditions. The existing work focuses on inferring the health of the robot during operation with little regard toward the defective element of the components. This article illustrates the detection of specific element damage of a robotic gearbox during a robotic cycle based on domain knowledge and presents a novel data-driven method for asset health. This starts by studying the robotic gearbox, specifically its kinematics as a planetary 2-stage reduction gearbox to acquire the knowledge of the rotations of each component. The signals acquired from a test bench with four sensors undergo different acquisition methods and signal processing techniques to correlate the elements’ frequencies. The work shows the detection of the artificially created defects from the acquired vibration data, verifying the kinematic methodology and identifying the root cause of failure of such gearboxes. A novel resampling method, Binning, is presented and compared with the traditional signal processing techniques. Binning combined with Principal Component Analysis (PCA) as a data-driven method to infer the state of the gearbox is presented, tested, and validated. This work presents methods as a step toward automatized predictive maintenance on robots in industrial applications.

Time-optimal trajectory generation in joint space for 6R industrial serial robots using Cuckoo search algorithm

The trajectory planning problem in industrial robotic applications has recently attracted the great attention of many researchers. In this paper, an optimal trajectory planning approach is proposed based on optimal time by utilizing the interpolation spline method. The method including a combination of cubic spline and 7th order polynomial is used for generating the trajectory in joint space for robot manipulators. Cuckoo Search (CS) optimization algorithm is chosen to optimize the joint trajectories based on objective, including minimizing total traveling time along the whole trajectory. The spline method has been applied to the PUMA robot for optimizing the joint trajectories with the CS algorithm based on the objective. With the trajectory planning method, the joint velocities, accelerations, and jerks along the whole trajectory optimized by CS meet the requirements of the kinematic constraints in the case of the objective. Simulation results validated that the used trajectory planning method based on the proposed algorithm is very effective in comparison with the same methods based on the algorithms proposed by earlier authors. Keywords: CS; industrial robots; interpolation; spline methods; trajectory planning.

Analysis of Position, Pose and Force Decoupling Characteristics of a 4-UPS/1-RPS Parallel Grinding Robot

For the application of parallel robots in the grinding industry, a parallel robot equipped with a constant force actuator that produces a constant force for grinding is designed. To study the characteristics of the parallel robot’s spatial positions and poses, the inverse solutions of the moving platform’s spatial positions and poses as well as the workspace where objects were ground were established by using DH parameters and geometric methods. The experimental results showed that the workspace where objects were ground was a cylinder with a cross section similar to a symmetric circular sector. To analyze the characteristics of the forces produced by the parallel robotic system, the dynamics equation was established via the Newton–Euler method to verify the rationality of the force decoupling design. Theoretical calculation combined with simulation and experimental analyses confirmed the viability of the theoretical analyses which lay a theoretical foundation for the design, manufacture and control of the parallel robotic system proposed in this paper.

An extendable framework for intelligent and easily configurable skills-based industrial robot applications

Modern, flexible, and easy-to-use robotic technologies have the potential to support companies to increase their productivity within today’s dynamic and volatile production. In this context, we introduce a skills-based software framework that makes it possible to configure the functional capabilities of industrial robots flexibly. In addition, we have structured the software framework into three consecutive expansion stages. In this way, it is possible to expand the robot’s reasoning capabilities step by step so that the robot is enabled to be instructed at higher abstraction levels and to process increasingly complex tasks. The contribution of our work is the further development of previous approaches and ideas from the research field of skills-based industrial robotic frameworks by considering new and previously unaddressed design issues within the structure of our software framework. We demonstrate the application of the framework using the example of an industrial robot for assembling a diverse range of LEGO products. The example of use consists of three consecutive scenarios. To begin with, the robot assembles different predefined product variants. Subsequently, we extend the robot application in a step-by-step manner to allow the robot to execute more and more complex tasks until it can finally plan individual tasks autonomously. On the one side, our approach shows how to enable companies with little robotic experience to start developing robotic applications and thereby gain further expertise. On the other side, by using this approach the effort and time for developing industrial robot applications will be reduced in the long term.

Simulation Data Driven Design Optimization for Reconfigurable Soft Gripper System

In the soft gripper design work, most of the designs such as gripping width and the design of finger actuator are purely based on experience, and repeated trial-and-error. In most scenarios, the designed actuators cannot achieve the best/optimized grasping performance with a specific design type. This optimized design is important especially for the food grasping application, as a minor improvement of the grasping capability will be helpful to increase the grasping success ratio, especially during high-speed pick and place tasks. That motivates us to develop a design optimization framework, focusing on how to achieve an optimized grasping performance with a multi-objective design optimization. In this work, a simulation aided data-driven optimization framework for guiding the design of a reconfigurable soft gripper system is presented. To achieve an effective optimization, a simulation model is developed based on the Simulation Open Framework Architecture (SOFA) platform. This model can predict the bending and grasping behavior under actuation and external loading. This model is then used in a data-driven design optimization framework for optimizing the actuator design. An artificial neural network (ANN) is built based on the simulation results as training data, and used as a surrogate model in a multi-objective optimization framework, to achieve an optimal grasping capability with design constraints. This simulation and optimization capability can significantly reduce the trial-and-error design work, and has a great potential for effectively developing soft robots in industrial applications, such as food manufacturing and health care.

Path discovering in maze area using mobile robot

Robotic maze pathfinding problems deal with detecting the correct route from the start point to the end-point in a virtual maze environment consisting of walls. Automated robot mobility is a significant feature, which enables a mobile robot to traverse a maze independently, from one position to another, without human intervention. There is a myriad of autonomous industrial mobile robot applications, including the transportation of goods and parts, domestic cleaning, indoor security surveillance, airport baggage couriering, and a plethora of other applications to traverse dangerous locations. This paper proposes a pathfinding mobile robot in a virtual maze based on a combination of a simplified left-hand algorithm and a line-following control algorithm. The mobile robot works in any maze to determine a route from the initial starting point to the end-point. The approach outlined in this paper uses a left-hand algorithm to solve the maze problem and a line-follower control algorithm to enable the robot to move in a straight line through the virtual maze. The algorithm used is less complicated and prevents the robot from falling into infinity loops compared to the traditional wall-follower algorithm.

Development and Implementation of a Collaborative Workspace for Industrial Robots Utilizing a Practical Path Adaptation Algorithm and Augmented Reality

The idea of humans and robots coexisting in manufacturing environments has increased the importance of personnel safety. Current practice to provide human safety in a conventional industrial robotic application is to put the robot in a cell enclosed by fences that occupies a large area in the environment. If someone enters this robotic cell, the robot ceases its movement immediately that leads to significant delays in the production cycle. In this paper, we present a new collaborative workspace concept for conventional industrial robots in order to eliminate fences and to avoid delays as much as possible. The proposed concept relies on a novel path adaptation algorithm and an augmented reality-based warning system. The algorithm, which makes the robot adaptable to human interventions, is unique in a sense that it can be applied to variety of industrial robots without requiring changes in the robot controller. Besides, the warning system provides additional safety features to the collaborative workspace through a projector and a head-mounted display. We demonstrate the feasibility of the proposed concept with an industrial robot in a realistic palletizing application. Several experiments were carried out to test the performance along with a user study. Performance test results indicate that the robot is able to perform three actions according to the minimum distance between the human and the robot in case of a human violation: slowdown, avoidance, and full stop. Qualitative performance tests results show that augmented reality improves the perception of safety and collaboration but negatively affects physical comfort. Overall, the proposed concept provides a practical and implementable solution for conventional industrial robots missing collaborative features.

Robot tangram assembly line based on vision

With the development of smart manufacturing technology, the cost of industrial robots is reduced and reliability enhanced. Applying several robots for automated production lines will be more popular. The extended application of industrial robots can improve the level of automation in industrial production and break the boundaries of technology and costs. The project focuses on "Tangram assembly line". This project takes "tangram assembly line" as the research object, and uses the kinematics model and path planning method of industrial robots to complete the identification, assembly and disassembly of tangram. "Tangram" simulated industrial products, based on two-dimensional vision to carry out image processing, identify the position and Angle of the object information, through writing robot program, the final completion of the object splicing and disassembly work. CoppeliaSim Edu software simulation results prove that the project can be efficient, high quality to complete the expected task.

Does the application of industrial robots overcome the Solow paradox? Evidence from China

With the development of the industrial robot, has its application promoted China's total factor productivity? Does it overcome the Solow paradox? Based on China's provincial panel data from 2006 to 2019, this study systematically examines the impact of industrial robot application on the total factor productivity in different regions. The empirical results of this study indicate: (ⅰ) there is a U-shaped relationship between the application of industrial robots and the total factor productivity, and the provinces whose industrial robot installation density exceeds the U-shaped turning point account for 61.19%; (ⅱ) for the robustness test section, we use the IV-2SLS, DOLS, FMOLS methods and replace the dependent variable to re-estimate the empirical analysis, and the results are the same as the baseline regression; (ⅲ) the transmission mechanism results show that industrial robot application promotes the total factor productivity by improving human capital and information technology, while aging has a negative effect on the total factor productivity; (iv) finally, the spatial effect test shows that the application of industrial robots on the total factor productivity has a U-shaped relationship in local areas, while it has an inverted U-shaped relationship in the neighboring regions.

Dynamic behavior and path accuracy of an industrial robot with a CNC controller

The application of industrial robots in the field of machining is gradually increasing, but their low absolute position accuracy and low stiffness affect the improvement of machining accuracy. Computer numerical control (CNC) has good performance to control the motion accuracy in the machine tool. Therefore, it is proposed to improve the motion accuracy of robots. This article utilizes a stereo high-speed camera to track robot motion. Circular paths running under the CNC system are planned to evaluate its performance, which includes path accuracy, motion velocity, and acceleration. The performance of identical paths running in a conventional robot controller is evaluated for comparison. Based on the experimental analysis, the CNC system, which has more functionalities for acceleration regulation, can get better path accuracy and stability. It indicates that acceleration control has a significant effect on path accuracy and motion velocity. The acceleration profile in a conventional robot controller resembles a triangle. By default, the maximum acceleration value is adopted for the motion planning. Therefore, its accelerating and decelerating phase is much shorter than that of the CNC system, which could lead to instability. Both Step-shaped and trapezoidal acceleration profiles in the CNC system improve the dynamic behavior of the robot. Considering the trade-off between path accuracy and motion velocity, the Step-shaped acceleration profile can be applied to the optimization of the traditional robot motion control.

Robust design of independent joint control of industrial robots with secondary encoders

The independent joint control approach with motor-side velocity and position feedback still dominates most industrial robot applications. Although it is known, that the elasticity of the drivetrains has a significant influence on the achievable dynamic path accuracy. As a result, an increasing number of industrial robots are available that use secondary encoders to measure the joint position. This paper addresses the robust design of independent joint control of industrial robots with secondary encoders under explicit consideration of the drivetrain elasticity. For this purpose, the nonlinear robot dynamics are linearized and the configuration dependency of the mass matrix is treated as structured uncertainty. The trade-off between the velocity control bandwidth and the gain margin of the position control loop is solved by means of a nonsmooth optimization-based H∞ synthesis. The design method is validated for the three base joints of a KUKA KR210-2 industrial robot. Experimental results for linear Cartesian paths and a milling experiment are presented to confirm the approach.

Manufacturing and controlling 5-axis ball screw driven industrial robot moving through G codes

These days, in industrial robot applications, servo motors with reducer have been used to move robot manipulators. Due to the weight of the robot parts, it causes undesirable conditions such as backward movement, downward movement and vibration caused by the moments of inertia at the time of movement. In this study, step motor ball screw driven actuators, which use push-pull force instead of servo motor with reducers, were utilized to provide rotational movement in robot arms. The ball screw system reduces the effect of moments of inertia caused by the movements of the robot joints, and restricts the free movements of the robot joints. It also provides an advantage by reducing costs since it uses smaller motors. In articulated robots, the complexity of kinematic equations and the use of high-order polynomials for trajectory planning cause difficulties in controlling. In this study, the information of the points, where the robot went during the manual movement, was obtained by using the macros prepared in program interface without using kinematic and trajectory planning equations. The position lines taken at these points were printed in a text file by adding the code G01 and f feed-rate. The robot was made to move by running this file in the program interface used for control. This method allows the operator to use the robot without advanced kinematics knowledge.

Optimizing Cycle Time of Industrial Robotic Tasks with Multiple Feasible Configurations at the Working Points

Industrial robot applications should be designed to allow the robot to provide the best performance for increasing throughput. In this regard, both trajectory and task order optimization are crucial, since they can heavily impact cycle time. Moreover, it is very common for a robotic application to be kinematically or functionally redundant so that multiple arm configurations may fulfill the same task at the working points. In this context, even if the working cycle is composed of a small number of points, the number of possible sequences can be very high, so that the robot programmer usually cannot evaluate them all to obtain the shortest possible cycle time. One of the most well-known problems used to define the optimal task order is the Travelling Salesman Problem (TSP), but in its original formulation, it does not allow to consider different robot configurations at the same working point. This paper aims at overcoming TSP limitations by adding some mathematical and conceptual constraints to the problem. With such improvements, TSP can be used successfully to optimize the cycle time of industrial robotic tasks where multiple configurations are allowed at the working points. Simulation and experimental results are presented to assess how cost (cycle time) and computational time are influenced by the proposed implementation.

A Stereo Matching Algorithm for High‐Precision Guidance in a Weakly Textured Industrial Robot Environment Dominated by Planar Facets

AbstractAlthough many algorithms perform very well on certain datasets, existing stereo matching algorithms still fail to obtain ideal disparity images with high precision in practical robotic applications with weak or untextured objects. This greatly limits the application of binocular vision for robotic arm guidance. Traditional stereo matching algorithms suffer from disparity loss, dilation and other problems, and deep learning algorithms have weakly generalization ability, making high‐accuracy results impossible with non‐training images. We propose an algorithm that uses segments and edges as matching units. We find the mapping relationship between two‐dimensional images and three‐dimensional scenes using segments. The algorithm obtains highly accurate results in industrial robotic applications with mainly planar facets. We combine it with a deep learning algorithm to obtain very good high‐accuracy results in both general scenes and applications of industrial robots. The algorithm effectively improves the non‐linear optimization ability of traditional algorithms and generalization ability of deep learning, and provides an effective method for the binocular vision guidance of industrial robotic scenes. We used the algorithm to guide the robot arm for threading with a success rate of 70%.

The Impact of Industrial Robots on the Skill-Based Wage Gap

In recent years, with the disappearance of the demographic dividend of the aging society and the requirements for high-quality economic development under the new normal, the application of industrial robots has rapidly advanced in the Chinese market. As an emerging driving force of technological progress, artificial intelligence has its own technological bias, but the existing literature has not paid attention to whether this bias will widen the income distribution gap of labor with heterogeneous skills. Based on this, this paper uses the panel data of 30 provinces from 2006 to 2015 to describe the application level of industrial robots with the import volume of industrial robots, and establishes a macro proxy indicator of skill-based wage gap according to the data of different skill industries to test the industrial robots in the Chinese context, using real effects on skills wage gaps, and conducting an analysis of geographic heterogeneity. In addition, further investigate the mechanism by which intelligent equipment exacerbates the skill-based wage gap, and analyze the possible “substitution effect”, “demand effect” and “asymmetric labor productivity effect” of the use of industrial robots on the skilled labor force. The results show that the use of industrial robots has a significant positive effect on the expansion of the skill-based wage gap. The use of industrial robots will exacerbate the wage gap between the high-skilled and low-skilled labor in the market. This effect comes from a combination of three effects: the “substitution effect”—the use of industrial robots will change the skill structure of employment, reducing the proportion of low-skilled workers; the “demand effect”—the use of industrial robots will change to some extent. The increase in demand for high-skilled labor has no significant impact on the demand for low-skilled labor.

Analysis of the application of industrial robots in intelligent manufacturing

In the context of the new era, industrial robots play an increasingly important role in the field of intelligent manufacturing, which not only boosts the high-quality development of China's economy, but also helps promote the optimization and upgrading of industrial structure and enhance the momentum of economic development. At present, industrial robots are widely used in intelligent manufacturing in welding operation, automobile manufacturing, automatic assembly and other aspects, and have formed a certain industrial scale and economic effect. Therefore, this article mainly from the industrial robot in the field of intelligent manufacturing development present situation, analyzes the industrial robot in the field of intelligent manufacturing applications, and put forward from the stick to establish and improve the personnel training mechanism, vigorously strengthen the technological innovation capability and upgrading product application performance and so on three aspects to explore the optimum path of industrial robots in the field of intelligent manufacturing, In order to promote the long-term development of industrial robots from the perspective of intelligent manufacturing in the future.