scholarly journals Fuzzy Interpolation and Other Interpolation Methods Used in Robot Calibrations

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Ying Bai ◽  
Nailong Guo ◽  
Gerald Agbegha

A novel interpolation algorithm, fuzzy interpolation, is presented and compared with other popular interpolation methods widely implemented in industrial robots calibrations and manufacturing applications. Different interpolation algorithms have been developed, reported, and implemented in many industrial robot calibrations and manufacturing processes in recent years. Most of them are based on looking for the optimal interpolation trajectories based on some known values on given points around a workspace. However, it is rare to build an optimal interpolation results based on some random noises, and this is one of the most popular topics in industrial testing and measurement applications. The fuzzy interpolation algorithm (FIA) reported in this paper provides a convenient and simple way to solve this problem and offers more accurate interpolation results based on given position or orientation errors that are randomly distributed in real time. This method can be implemented in many industrial applications, such as manipulators measurements and calibrations, industrial automations, and semiconductor manufacturing processes.

2021 ◽  
Author(s):  
Rishi Malhan ◽  
Rex Jomy Joseph ◽  
Prahar M. Bhatt ◽  
Brual Shah ◽  
Satyandra K. Gupta

Abstract 3D reconstruction technology is used in a wide variety of applications. Currently, automatically creating accurate pointclouds for large parts requires expensive hardware. We are interested in using low-cost depth cameras mounted on commonly available industrial robots to create accurate pointclouds for large parts automatically. Manufacturing applications require fast cycle times. Therefore, we are interested in speeding up the 3D reconstruction process. We present algorithmic advances in 3D reconstruction that achieve a sub-millimeter accuracy using a low-cost depth camera. Our system can be used to determine a pointcloud model of large and complex parts. Advances in camera calibration, cycle time reduction for pointcloud capturing, and uncertainty estimation are made in this work. We continuously capture point-clouds at an optimal camera location with respect to part distance during robot motion execution. The redundancy in pointclouds achieved by the moving camera significantly reduces errors in measurements without increasing cycle time. Our system produces sub-millimeter accuracy.


2019 ◽  
Vol 71 (1) ◽  
pp. 9-13 ◽  
Author(s):  
Alexandru Bârsan

Abstract The approach of this paper was to analyze the technical borders of industrial robots and to provide an overview of current technology, technical constraints and the potential types of future research suggestion concerning robotic machining. These complex automation machines used in manufacturing processes are an emerging chapter of industrial engineering that contribute to automatically performing operation in subtractive manufacturing and sheet metal forming processes. Compared with CNC machines which have shape limitations and have the restricted working area, the industrial robot is a flexible, cost-saving alternative.


2021 ◽  
Author(s):  
Juan Sebastian Toquica ◽  
José Maurı́cio Motta

Abstract This paper proposes a methodology for calibration of industrial robots that uses a concept of measurement sub-regions, allowing low-cost solutions and easy implementation to meet the robot accuracy requirements in industrial applications. The solutions to increasing the accuracy of robots today have high-cost implementation, making calibration throughout the workplace in industry a difficult and unlikely task. Thus, reducing the time spent and the measured workspace volume of the robot end-effector are the main benefits of the implementation of the sub-region concept, ensuring sufficient flexibility in the measurement step of robot calibration procedures. The main contribution of this article is the proposal and discussion of a methodology to calibrate robots using several small measurement sub-regions and gathering the measurement data in a way equivalent to the measurements made in large volume regions, making feasible the use of high-precision measurement systems but limited to small volumes, such as vision-based measurement systems. The robot calibration procedures were simulated according to the literature, such that results from simulation are free from errors due to experimental setups as to isolate the benefits of the measurement proposal methodology. In addition, a method to validate the analytical off-line kinematic model of industrial robots is proposed using the nominal model of the robot supplier incorporated into its controller.


2020 ◽  
Vol 10 (13) ◽  
pp. 4619 ◽  
Author(s):  
Matteo Bottin ◽  
Silvio Cocuzza ◽  
Nicola Comand ◽  
Alberto Doria

The stiffness properties of industrial robots are very important for many industrial applications, such as automatic robotic assembly and material removal processes (e.g., machining and deburring). On the one hand, in robotic assembly, joint compliance can be useful for compensating dimensional errors in the parts to be assembled; on the other hand, in material removal processes, a high Cartesian stiffness of the end-effector is required. Moreover, low frequency chatter vibrations can be induced when low-stiffness robots are used, with an impairment in the quality of the machined surface. In this paper, a compliant joint dynamic model of an industrial robot has been developed, in which joint stiffness has been experimentally identified using a modal approach. First, a novel method to select the test configurations has been developed, so that in each configuration the mode of vibration that chiefly involves only one joint is excited. Then, experimental tests are carried out in the selected configurations in order to identify joint stiffness. Finally, the developed dynamic model of the robot is used to predict the variation of the natural frequencies in the workspace.


Author(s):  
Cong Wang ◽  
Chung-Yen Lin ◽  
Masayoshi Tomizuka

Vision guided robots have become an important element in the manufacturing industry. In most current industrial applications, vision guided robots are controlled by a look-then-move method. This method cannot support many new emerging demands which require real-time vision guidance. Challenge comes from the speed of visual feedback. Due to cost limit, industrial robot vision systems are subject to considerable latency and limited sampling rate. This paper proposes new algorithms to address this challenge by compensating the latency and slow sampling of visual feedback so that real-time vision guided robot control can be realized with satisfactory performance. Statistical learning methods are developed to model the pattern of target's motion adaptively. The learned model is used to recover visual measurement from latency and slow sampling. The imaging geometry of the camera and all-dimensional motion of the target are fully considered. Tests are conducted to provide evaluation from different aspects.


Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1431
Author(s):  
Germán Andrés Ramos ◽  
Tomàs Montobbio de Pérez-Cabrero ◽  
Carles Domènech-Mestres ◽  
Ramon Costa-Castelló

Electric vehicles are becoming more and more popular. One of the most promising possible solutions is one where a hybrid powertrain made up of a FC (Fuel Cell) and a battery is used. This type of vehicle offers great autonomy and high recharging speed, which makes them ideal for many industrial applications. In this work, three ways to build a hybrid power-train are presented and compared. To illustrate this, the case of an industrial robot designed to move loads within a fully automated factory is used. The analysis and comparison are carried out through different objective criteria that indicate the power-train performance in different battery charge levels. The hybrid configurations are tested using real power profiles of the industrial robot. Finally, simulation results show the performance of each hybrid configuration in terms of hydrogen consumption, battery and FC degradation, and dc bus voltage and current regulation.


Author(s):  
Mohsen Moradi Dalvand ◽  
Saeid Nahavandi

Purpose – The purpose of this paper is to analyse teleoperation of an ABB industrial robot with an ABB IRC5 controller. A method to improve motion smoothness and decrease latency using the existing ABB IRC5 robot controller without access to any low-level interface is proposed. Design/methodology/approach – The proposed control algorithm includes a high-level proportional-integral-derivative controller (PID) controller used to dynamically generate reference velocities for different travel ranges of the tool centre point (TCP) of the robot. Communication with the ABB IRC5 controller was performed utilising the ABB PC software development kit. The multitasking feature of the IRC5 controller was used to enhance the communication frequency between the controller and the remote application. Trajectory tracking experiments of a pre-defined three-dimensional trajectory were carried out and the benefits of the proposed algorithm were demonstrated. The robot was intentionally installed on a wobbly table and its vibrations were recorded using a six-degrees-of-freedom force/torque sensor fitted to the tool mounting interface of the robot. The robot vibrations were used as a measure of the smoothness of the tracking movements. Findings – A communication rate of up to 250 Hz between the computer and the controller was established using C# .Net. Experimental results demonstrating the robot TCP, tracking errors and robot vibrations for different control approaches were provided and analysed. It was demonstrated that the proposed approach results in the smoothest motion with tracking errors of < 0.2 mm. Research limitations/implications – The proposed approach may be employed to produce smooth motion for a remotely operated ABB industrial robot with the existing ABB IRC5 controller. However, to achieve high-bandwidth path following, the inherent latency of the controller must be overcome, for example by utilising a low-level interface. It is particularly useful for applications including a large number of short manipulation segments, which is typical in teleoperation applications. Social implications – Using the proposed technique, off-the-shelf industrial robots can be used for research and industrial applications where remote control is required. Originality/value – Although low-level control interface for industrial robots seems to be the ideal long-term solution for teleoperation applications, the proposed remote control technique allows out-of-the-box ABB industrial robots with IRC5 controllers to achieve high efficiency and manipulation smoothness without requirements of any low-level programming interface.


Author(s):  
Guilherme Boulhosa Rodamilans ◽  
Emília Villani ◽  
Luís Gonzaga Trabasso ◽  
Wesley Rodrigues de Oliveira ◽  
Ricardo Suterio

Purpose This paper aims to propose an evaluation method to compare two different Human–Robot Interaction (HRI) solutions that can be used for on-line programming in an industrial context: a force guidance system and the traditional teach pendant operation. Design/methodology/approach The method defines three evaluation criteria (agility, accuracy and learning) and describes an experimental approach based on the analysis of variance to verify the performance of guidance systems according to these criteria. This method is used in this paper to compare the traditional teach pendant interface with an implementation of a force guidance system based on the use of an external force/torque sensor. Findings The application of the proposed method to an off-the-shelf industrial robot shows that the force guidance system has a better performance according to the agility criterion. Both solutions have a similar performance for the accuracy criterion, with a limit of about 2 mm in the achieved position accuracy. Regarding the learning criterion, the authors cannot affirm that any of the methods has an improved agility when the operator repeats the tasks. Practical implications This work supports the selection of guidance systems to be used in on-line programming of industrial applications. It shows that the force guidance system is an option potentially faster than the teach pendant when the required positioning accuracy is greater than 2 mm. Originality/value The new method proposed in this paper can be applied to a large range of robots, not being limited to commercial available collaborative robots. Furthermore, the method is appropriate to accomplish further investigations in HRI not only to compare programming methods but also to evaluate guidance systems approaches or robot control systems.


2021 ◽  
Vol 15 (5) ◽  
pp. 565-566
Author(s):  
Soichi Ibaraki ◽  
Andreas Archenti

The industrial robot is more precisely an “automatically controlled, reprogrammable, multipurpose manipulator, programmable in three or more axes, which can be either fixed in place or mobile” (ISO 8373:2012). According to the International Federation of Robotics, by 2018, more than 400,000 new units were being installed annually, and the global average robot density in the manufacturing industry was 99 robots per 10,000 employees. More than 30% of all installed robots were in the automotive industry, the biggest customer for robots. Research on measuring and calibrating, modeling, programming and controlling, and integrating systems has been conducted to give robotic manipulators a wider variety of industrial applications. This special issue covers technical and academic efforts related to new technologies that improve the accuracy and facilitate the implementation of robotic manipulators in industrial applications. The first paper, by Ibaraki et al., outlines technical issues and future research directions for the implementation of model-based numerical compensation schemes for industrial robots. The random forest method is used by Kato et al. to construct a calibration model for positioning errors and identify industrial robots’ positioning errors. A procedure for the quasi-static compliance calibration of serial articulated industrial manipulators is proposed by Theissen et al. A review of the kinematic modeling theory and a derived algorithm to identify error sources for a six-axis industrial robot are presented by Alam et al. Nagao et al. derive a forward kinematics model and identify the kinematics parameters for the calibration of a robot-type machine tool. A novel trajectory generation algorithm, including a corner smoothing method for high-speed and high-accuracy machining by industrial robots, is proposed by Tajima et al. Sato et al. study the vibration characteristics of an industrial robot and derive a mathematical model that represents the dynamic behavior of the system. In the context of smart manufacturing, a multilayer quality inspection framework including a measurement instrument and a robot manipulator is introduced by Azamfirei et al. To support mass customization and the development of reconfigurable manufacturing systems, Inoue et al. propose an autonomous mobile robotic manipulator. Yonemoto and Suwa present an adaptive manipulation procedure to establish an automated scheduling technique that flexibly responds to unforeseen events, such as machine failures. Sasatake et al. introduce a learning system that is based on a method for calculating the similarity between tools, and they test it on a robot system for doing housework. Finally, for better knowledge of the key challenges that manufacturers experience in implementing collaborative industrial robots, an industrial survey is conducted by Andersson et al. The editors sincerely appreciate the contributions of all the authors as well as the work of the reviewers. We are confident that this special issue will further encourage research and engineering work to increase our understanding and knowledge of robotic manipulators and their industrial applications.


2015 ◽  
Vol 6 (2) ◽  
pp. 245-254 ◽  
Author(s):  
M. Oberherber ◽  
H. Gattringer ◽  
A. Müller

Abstract. The time optimal path tracking for industrial robots regards the problem of generating trajectories that follow predefined end-effector (EE) paths in shortest time possible taking into account kinematic and dynamic constraints. The complicated tasks used in industrial applications lead to very long EE paths. At the same time smooth trajectories are mandatory in order to increase the service life. The consideration of jerk and torque rate restrictions, necessary to achieve smooth trajectories, causes enormous numerical effort, and increases computation times. This is in particular due to the high number of optimization variables required for long geometric paths. In this paper we propose an approach where the path is split into segments. For each individual segment a smooth time optimal trajectory is determined and represented by a spline. The overall trajectory is then found by assembling these splines to the solution for the whole path. Further we will show that by using splines, the jerks are automatically bounded so that the jerk constraints do not have to be imposed in the optimization, which reduces the computational complexity. We present experimental results for a six-axis industrial robot. The proposed approach provides smooth time optimal trajectories for arbitrary long geometric paths in an efficient way.


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