Current Industrial Robots Research Articles

The Expanding Role of Artificial Intelligence in Collaborative Robots for Industrial Applications: A Systematic Review of Recent Works

A collaborative robot, or cobot, enables users to work closely with it through direct communication without the use of traditional barricades. Cobots eliminate the gap that has historically existed between industrial robots and humans while they work within fences. Cobots can be used for a variety of tasks, from communication robots in public areas and logistic or supply chain robots that move materials inside a building, to articulated or industrial robots that assist in automating tasks which are not ergonomically sound, such as assisting individuals in carrying large parts, or assembly lines. Human faith in collaboration has increased through human–robot collaboration applications built with dependability and safety in mind, which also enhances employee performance and working circumstances. Artificial intelligence and cobots are becoming more accessible due to advanced technology and new processor generations. Cobots are now being changed from science fiction to science through machine learning. They can quickly respond to change, decrease expenses, and enhance user experience. In order to identify the existing and potential expanding role of artificial intelligence in cobots for industrial applications, this paper provides a systematic literature review of the latest research publications between 2018 and 2022. It concludes by discussing various difficulties in current industrial collaborative robots and provides direction for future research.

Space robot motion path planning based on fuzzy control algorithm

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.

Position domain control technology for six-joint robots

In the context of the rapid development of intelligent manufacturing, high-precision motion control of industrial robots has attracted increasing research attention. High-speed and high-precision motion control is a development trend associated with the current industrial robots. Industrial transformation and upgradation can be accelerated only via the independent research and development of robot core technologies, including robot high-precision control systems, ensuring the transition of the manufacturing industry in China toward intelligent and digital development. Currently, the contour tracking error associated with majority of the multiaxes CNC machine tools and multijoint industrial robots is a common problem. A good tracking performance can be achieved in time with respect to each joint axis when the space trajectory of the serial multijoint industrial robot changes under multiaxes linkage. The ideal contour trajectory cannot be fully ensured because of the mechanical and electrical hysteresis effects. Therefore, the synchronization of the motion of each servo axis in the geometric space is very important. In this paper, the existing kinematics and dynamics of industrial robots were combined with the traditional PID control theory for studying position domain control algorithm of the six-joint robot to resolve the problem of low accuracy associated with the robot end profile, which can be attributed to the lag between the motion instruction and the actual position. The algorithm uses the method of real-time establishment of the master–slave motion relation for controlling the spatial contour trajectory of the robot. It further transforms the synchronization control method of each servo joint in the time domain into the master–slave follow control method of each servo joint in the position domain. While realizing synchronization control in the position domain, PD control based on position domain was introduced to reduce the following error of the master–slave following control, improving the overall accuracy of the contour motion of the robot end. The method proposed in this paper has been tested on the Linux CNC numerical control system with a company’s HSR-JR605 robot, indicating that the position of the domain control method employed positively affects the accuracy of six articulated robot space trajectory.

Investigation of the impact of various robot properties on a twin Robot-CT system

ABSTRACT Robot-CT is drawing great attention for its potential to support highly flexible scan trajectories and various scan modes with a single system. However, the quality of CT reconstruction largely depends on accurate knowledge of the scan geometry, i.e. position and orientation of the source and the detector. This imposes major challenges on current serial industrial robots. In order to realistically assess the impact of various robot characteristics on the Robot-CT reconstruction quality and to facilitate the development of a dedicated calibration method, this paper elaborates on a set of simulations based on the performance evaluation of an ABB industrial robot. Simulation results reveal that: (a) synchronous error motions of the twin robots can partially compensate for the robot errors; (b) offline calibration is a possible way to implement high accuracy Robot-CT due to the excellent repeatability of current industrial robots; (c) both robot positioning and orientation errors need to be compensated for to get a high quality reconstruction; (d) compensating for only the relative error cannot improve the final reconstruction quality: absolute positioning and orientation errors need to be measured and compensated for. External sensors or radiograph based absolute geometry calibration are needed to improve the reconstruction quality.

Optimal Experiment Design for Elasto-Geometrical Calibration of Industrial Robots

Inaccuracy of the kinematic model used in robot controllers and deflection of robot joints are two main sources of positioning errors in current industrial robots. We propose an elasto-geometrical calibration method to address these problems. The elasto-geometrical calibration identifies the accurate kinematic model and joint elasticities of any industrial serial robot by measuring the robot tool position at multiple design points. Each design point indicates a unique combination of a robot configuration (set of joint values) and an external load on the robot tool. Proper selection of the design points could significantly improve the calibration accuracy and reduce the experiment time. We propose an optimal design of experiment to find the D-, A-, and E-optimal designs from a large pool of candidate design points. Unlike the existing approaches, we use a semidefinite convex programming that can find a suboptimal design of experiments. The efficiency of the proposed elasto-geometrical calibration is evaluated on an ABB IRB 1600 robot. For this experiment, a cable-driven parallel robot is employed to apply multidirectional external loads on the tool of the ABB robot. Experimental results show that the proposed calibration method significantly improves the robot's accuracy in comparison with a regular kinematic calibration method. In addition, the D-optimal design results in less positioning error than A- and E-optimal designs.

Industrial robots for teleoperated surgery – a systematic review of existing approaches

Abstract Robotic assistance in surgical interventions has been shown to improve both the surgical outcome and the surgeon’s performance. However, cost-efficient implementation of such systems in an operating room workflow is not yet resolved. Most of the current approaches use highly specialized and purpose-built robotic components, resulting in large costs. This paper presents an investigation into the usage of off-the-shelf robots as cost-efficient basis for teleoperated surgery. In addition, the modifications required of the robot and/or operating environment to make it suitable for the medical setting are assessed. The considered systems are found via a literature search and the MERODA-database, specifically focusing on systems designed for teleoperated surgery which use industrial robots. Among the 126 telemanipulated systems found, only 10 use industrial robots for surgical procedures. Overall, due to the better availability, reduced costs, and increased performance, current industrial robots should be further considered for new and versatile lowcost approaches to teleoperated surgery.

Free-Form Surface Analysis and Linking Strategies for High Registration Accuracy in Quality Assurance Applications

Robot-based optical inspection systems have become more affordable and show great potential for measuring geometric features of sheet metal parts in production sites. To deal with the lack of positioning accuracy of current industrial robots for the registration of range images, a stitching algorithm is often applied. This paper presents a concept to improve the fine registration accuracy in order to reduce the effect of error propagation. A geometric analysis of the surface is introduced to identify suitable regions for applying adapted texture projections onto the part. In addition, an approach to develop a corresponding linking strategy is described. The proposed concept promises to measure geometric features on both plane and highly featured surfaces with high accuracy.

Supervised Learning of Human Welder Behaviors for Intelligent Robotic Welding

Current industrial welding robots are mostly articulated arms with a pre-programmed set of movement, which lack the intelligence skilled human welders possess. In this paper, human welder's response against 3-D weld pool surface is learned and transferred to the welding robots to perform automated welding tasks. To this end, an innovative teleoperated virtualized welding platform is utilized to conduct dynamic training experiments by a human welder whose arm movements together with the 3-D weld pool characteristic parameters are recorded. The data is off-line rated by the welder and a fuzzy classifier is trained, using an adaptive neuro-fuzzy inference system (ANFIS), to automate the rating. Data from the training experiments are then automatically classified such that top rated data pairs are selected to model and extract “good response” minimizing the effect from “bad operation” made during the training. A supervised ANFIS model is then proposed to correlate the 3-D weld pool characteristic parameters and welder's adjustment on the welding speed. The obtained model is then transferred to the welding robot to perform automated welding task as an intelligent controller. Experiment results verified that the proposed model is able to control the process under different welding current as well as under disturbances in speed and measurement. A foundation is thus established to selectively learn “good response” to rapidly extract human intelligence to transfer into welding robots.

Fusing machine algorithm with welder intelligence for adaptive welding robots

Current industrial welding robots are mostly articulated arms with a pre-programmed set of movement. These robots lack the adaptation and intelligence skilled human welders possess. With the recent developments in measuring 3D weld pool surface in GTAW, the critical process feedback available to human welders also becomes available to welding robots. To effectively use this critical feedback to equip welding robots, welders’ responses to this critical feedback have been modeled. It is arguable that human may have better robustness against process certainties but machine algorithms may be designed to be quicker in response. Switching among them appropriately may improve the performance but should base on a scientific criterion. Further, fusing them together may even better perform than simply switching. In this paper, a criterion is established to automatically rate the performance from each of the three algorithms being fused – one machine algorithm and two human response models/algorithms. A fuzzy system has been proposed and established to fuse the decisions from these algorithms per their performance ratings. Simulation confirms the superiority of the fusion method to any of these three algorithms. Automated welding experiments conducted by welding robot verifies that the fusion based welding speed controller was robust under different welding currents and input disturbances. A foundation is thus established to developing next generation intelligent welding robots by fusing machine and human intelligence.

Research on Industrial Robot Teaching Pendant based on Android and its Realization

As the current industrial robots teaching systems have some disadvantages including high maintenance cost, poor portability and operational complexity, an industrial robot teaching system based on Android platform has been developed. The teaching pendant uses Android system equipment for industrial robot control terminal that the user is transmitted to the robot controller by operating the robot teaching will be achieved task command, the controller receives a corresponding command to control the movement of each axis of the robot to achieve each goal pose. The teach pendant can be programmed module, teaching language is used in the robot pose memory recording the coordinates of each target, and ultimately to run the program through the teach pendant control, teaching and playback functions. Teach and controllers communicate using TCP and UDP protocols, network communication across platforms through the socket, and add functionality and extend the heartbeat of many single-threaded communication function in communication. Experimental results show that this teaching system has the advantages of stable operations, simple operations as well as good portability. It will have a broad prospect of application.

Robot skills for manufacturing: From concept to industrial deployment

Due to a general shift in manufacturing paradigm from mass production towards mass customization, reconfigurable automation technologies, such as robots, are required. However, current industrial robot solutions are notoriously difficult to program, leading to high changeover times when new products are introduced by manufacturers. In order to compete on global markets, the factories of tomorrow need complete production lines, including automation technologies that can effortlessly be reconfigured or repurposed, when the need arises. In this paper we present the concept of general, self-asserting robot skills for manufacturing. We show how a relatively small set of skills are derived from current factory worker instructions, and how these can be transferred to industrial mobile manipulators. General robot skills can not only be implemented on these robots, but also be intuitively concatenated to program the robots to perform a variety of tasks, through the use of simple task-level programming methods. We demonstrate various approaches to this, extensively tested with several people inexperienced in robotics. We validate our findings through several deployments of the complete robot system in running production facilities at an industrial partner. It follows from these experiments that the use of robot skills, and associated task-level programming framework, is a viable solution to introducing robots that can intuitively and on the fly be programmed to perform new tasks by factory workers. HighlightsWe propose a conceptual model of robot skills and show how this differs from macros.We show how this approach can enable non-experts to utilize advanced robotic systems.Concrete industrial applications of the approach are presented, on advanced robot systems.

A six-axis robotic sample changer for high-throughput neutron powder diffraction and texture measurements

State-of-the-art neutron time-of-flight diffractometers at modern neutron sources allow sample throughput at rates of much less than one hour per sample. Automated sample changes with a high degree of reliability and flexibility are essential to assure safe operation and efficient use of available neutron flux. At the High-Pressure Preferred Orientation (HIPPO) diffractometer, a previous sample changer measured over 2300 texture and 400 powder samples at ambient conditions to study the properties of crystalline materials at the Lujan neutron scattering facility at the Los Alamos Neutron Science Center. Experience gained during operation of the sample changer for over a decade showed room for improvement and led to a new design using current industrial robot technology. Here, the new HIPPO versatile six-axis robotic sample changer for neutron powder diffraction experiments including texture measurements is presented.

Using Object’s Contour, Form and Depth to Embed Recognition Capability into Industrial Robots

Robot vision systems can differentiate parts by pattern matching irrespective of part orientation and location. Somemanufacturers offer 3D guidance systems using robust vision and laser systems so that a 3D programmed point canbe repeated even if the part is moved varying its location, rotation and orientation within the working space. Despitethese developments, current industrial robots are still unable to recognize objects in a robust manner; that is, todistinguish an object among equally shaped objects taking into account not only the object’s contour but also its formand depth information, which is precisely the major contribution of this research. Our hypothesis establishes that it ispossible to integrate a robust invariant object recognition capability into industrial robots by using image features fromthe object’s contour (boundary object information), its form (i.e., type of curvature or topographical surfaceinformation) and depth information (from stereo disparity maps). These features can be concatenated in order to forman invariant vector descriptor which is the input to an artificial neural network (ANN) for learning and recognitionpurposes. In this paper we present the recognition results under different working conditions using a KUKA KR16industrial robot, which validated our approach.

Kineto-Elasto Dynamic Analysis of Robot Manipulator Puma-560

Current industrial robots are made very heavy to achieve high Stiffness which increases the accuracy of their motion. However this heaviness limits the robot speed and in masses the required energy to move the system. The requirement for higher speed and better system performance makes it necessary to consider a new generation of light weight manipulators as an alternative to today's massive inefficient ones. Light weight manipulators require Less energy to move and they have larger payload abilities and more maneuverability. However due to the dynamic effects of structural flexibility, their control is much more difficult. Therefore, there is a need to develop accurate dynamic models for design and control of such systems.This project presents the flexibility and Kineto - Elasto dynamic analysis of robot manipulator considering deflection. Based on the distributed parameter method, the generalized motion equations of robot manipulator with flexible links are derived. The final formulation of the motion equations is used to model general complex elastic manipulators with nonlinear rigid-body and elastic motion in dynamics and it can be used in the flexibility analysis of robot manipulators and spatial mechanisms. Manipulator end-effector path trajectory, velocity and accelerations are plotted. Joint torques is to be determined for each joint trajectory (Dynamics) .Using joint torques, static loading due to link's masses, masses at joints, and payload, the robot arms elastic deformations are to be found by using ANSYS-12.0 software package. Elastic compensation is inserted in coordinates of robotic programming to get exact end-effectors path. A comparison of paths trajectory of the end-effector is to be plotted. Also variation of torques is plotted after considering elastic compensation. These torque variations are included in the robotic programming for getting the accurate end- effect or's path trajectory.

Research of a Kind of New Intelligent Robot Hand Material

In order to further enhancing the ratio of load of the current intelligent industrial robot to its weight, and making the structure and movement of the intelligent robot develop rapidly toward the modularization, flexibility and reconfigurable mode, a kind of new-type intelligent robot hand material with high strength, light mass and large damping is proposed in the paper. The new composition material and its performance are also introduced and discussed in detail. Based on it, the specific preparation method and technology of the new-type composite material are given. The experimental results show that the weight of the intelligent robot hand material proposed in the paper can reduce by about 30% under the premise of ensuring the good strength of the intelligent robot hand.

The View to the Current State of Robotics

The article deal about the development in the field of robotic research. The introduction suggests and summarizes actual development in robotics, which is heavily focused on the service and humanoid field in many applications. Next section of contribution is dealed to the development and is referred to its fundamental properties, which has current industrial robots.

Assembly on moving production line based on sensor fusion

PurposeThe purpose of this paper is to develop an intelligent robot assembly system for the moving production line. Moving production lines are widely used in many manufacturing factories, including automotive and general industries. Industrial robots are hardly used to perform any tasks on the moving production lines. One of the main reasons is that it is difficult for conventional industrial robots to adjust to any sort of change. Therefore, more intelligent industrial robotic systems have to be developed to adopt the random motion of the moving production lines. This paper presents an intelligent robotics system that performs an assembly process while the object is moving, using synergic combination of visual servoing and force control technology.Design/methodology/approachThe developed intelligent robotic system includes some rules to ensure the success of the assembly processes. Also visual servoing and force control are used to deal with the random motion of the moving objects. Since the objects on the moving production lines are moving with random speed, visual servoing is adopted to tracking the motion of the moving object. Force control is also integrated to control the motion of the robot and keep the robotic system compliant with the moving objects to avoid the damage of the whole system.FindingsThe developed intelligent robotic technology has been successfully implemented. The wheel loading process is used as example.Research limitations/implicationsSince the developed technology is based on the low‐level motion control, safety has to be considered. Currently, it is done by motion supervision.Practical implicationsThe developed technology can be used to perform assemblies in the moving production lines. Since the developed platform is based on the synergic combination of visual servoing and force control technology, it can be used in other areas, such as seam tracking and seat loading, etc.Originality/valueThis paper provides a practical solution of performing assemblies on the moving production lines, which is not available on the current industrial robot market.

Formulation for actuators' number enumeration for main planar structures in robotics

Mechanisms and Machines Theory (MMT) contributed greatly to planar and spatial mechanism synthesis with different degrees of freedom. Some of the current industrial robots with planar chains have a main structure created by the kinematic graphs of MMT. This paper deals with a formulation allowing computing the number of possibilities for actuators' attachment for planar pin-jointed main driving mechanisms in robotics. It is based on the sub-chains symmetries of structures taking into account the position of the actuator of the robot. Pairs of groups of mutually symmetrical mechanisms are detected. Thus, eliminating the symmetrical ones confines the number of possible configurations. Different cases of symmetries have been studied. Expressions for calculation of the number of actuator position of a mechanism are presented. They enable the reduction of the number of structures by avoiding those that are isomorphic. Following this, examples for applications for various planar pin-jointed kinematic structures are presented, enabling the field of research to be restricted to the possible solutions. La Théorie des Mécanismes et des Machines (TMM) a largement contribué dans la synthèse des mécanismes plans et spatiaux à différents degrés de mobilité. Certains robots industriels actuels ont des structures principales issues des graphes cinématiques fournis par la TMM. Ce papier concerne une formulation permettant un calcul restreint de mécanismes moteurs plans à liaisons pivots en robotique. Il est basé sur la notion de symétrie des structures concernant la position de l'actionneur du robot. Différents cas de combinaisons de couples de mécanismes symétriques sont détectés. Ainsi le nombre de configurations possibles est restreint par élimination de ceux qui sont symétriques. Différents cas de combinaisons de symétries sont étudiés. Des formulations pour calculer le nombre de possibilités d'ancrer un actionneur sont présentées. Elles permettent de réduire le nombre de structures tout en évitant celles qui sont isomorphes. Par la suite différents exemples d'application sont présentés permettant de restreindre le champ de recherche parmi les solutions possibles.

Suboptimal robot motion for inexperienced situations through intelligent composite motion control: Method of knowledge array

The intelligent composite motion control (ICMC) is a methodology to build up robot systems in which robots can realize complex and dexterous behaviours autonomously and adaptively by parameter optimization and utilization of experiential knowledge only if the motion control for fundamental element motions is given. In this paper, after reviewing the ICMC method of a knowledge array is presented, this is a method for realizing suboptimal motions for inexperienced situations by the use of experiential knowledge, in which the experiential knowledge is stored in the form of a knowledge array and is utilized to estimate suboptimal motions for inexperienced situations. The array is the generalization of the vector-matrix and it can easily and concisely express and perform such operations that are very difficult or impossible to be expressed in the conventional vector-matrix formulation. Therefore it is expected that the array will realize highly intelligent knowledge operations such as abstraction and broad interpretation. In the ICMC, all the robot behaviours from simple point to point (PTP) motions to complicated tasks are treated in a unified manner; thus the ICMC can be applied to current industrial robots as well as to future, much more complicated robot systems. It is shown that the method is effectively applied to the dextrous handling problem of flexible plates.

Implementation and experimental study of a multiprocessor system for real-time model-based robot motion control

This paper presents the design and implementation of a multiprocessor system for real-time robot motion control. Full inverse dynamics compensation control laws in both joint and Cartesian spaces are used for developing parallel computation algorithms. The algorithms are divided into subtasks which are distributed among a fixed number of processors based on heuristic scheduling algorithms. The control laws are real-time tested on an experimental robot. The results present a feasible way for improving controller performance of current industrial robots.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>