KCT: a MATLAB toolbox for motion control of KUKA robot manipulators

Abstract—The Kuka Control Toolbox (KCT) is a collection of MATLAB functions for motion control of KUKA robot manipulators, developed to offer an intuitive and high-level programming interface to the user. The toolbox, which is compatible with all 6 DOF small and low payload KUKA robots that use the Eth.RSIXML, runs on a remote computer connected with the KUKA controller via TCP/IP. KCT includes more than 30 functions, spanning operations such as forward and inverse kinematics computation, point-to-point joint and Cartesian control, trajectory generation, graphical display and diagnostics. The flexibility, ease of use and reliability of the toolbox is demonstrated through two applicative examples. I

Enabling robotic adaptive behaviour capabilities for new Industry 4.0 automated quality inspection paradigms

The seamless integration of industrial robotic arms with server computers, sensors and actuators can revolutionise the way in which automated non-destructive testing (NDT) is performed and conceived. Achieving effective integration and realising the full potential of robotic systems presents significant challenges, since robots, sensors and end-effector tools are often not necessarily designed to be put together and form a holistic system. This paper presents recent breakthroughs, opening up new scenarios for the inspection of product quality in advanced manufacturing. Many years of research have brought to software platforms the ability to integrate external data acquisition instrumentation with industrial robots to improve the inspection speed, accuracy and repeatability of NDT. Robotic manipulators have typically been operated by predefined tool-paths generated through offline path-planning software applications. Recent developments pave the way to data-driven autonomous robotic inspections, enabling real-time path planning and adaptive control. This paper presents a toolbox with highly efficient algorithms and software functions, developed to be used through high-level programming language platforms (for example MATLAB, LabVIEW and Python) and/or integrated within low-level language (for example C# and C++) applications. The use of the toolbox can speed up the development and the robust integration of new robotic NDT systems with real-time adaptive capabilities and is compatible with all KUKA robots with six degrees of freedom (DOF), which are equipped with the Robot Sensor Interface (RSI) software add-on. The paper describes the architecture of the toolbox and shows two application examples, where performance results are provided. The concepts described in the paper are aligned with the emerging Industry 4.0 paradigms and have wider applicability beyond NDT

Enabling robotic adaptive behaviour capabilities for new industry 4.0 automated quality inspection paradigms

The seamless integration of industrial robotic arms with server computers, sensors and actuators can revolutionise the way in which automated non-destructive testing (NDT) is performed and conceived. Achieving effective integration and realising the full potential of robotic systems presents significant challenges, since robots, sensors and end-effector tools are often not necessarily designed to be put together and form a holistic system. This paper presents recent breakthroughs, opening up new scenarios for the inspection of product quality in advanced manufacturing. Many years of research have brought to software platforms the ability to integrate external data acquisition instrumentation with industrial robots to improve the inspection speed, accuracy and repeatability of NDT. Robotic manipulators have typically been operated by predefined tool-paths generated through offline path-planning software applications. Recent developments pave the way to data-driven autonomous robotic inspections, enabling real-time path planning and adaptive control. This paper presents a toolbox with highly efficient algorithms and software functions, developed to be used through high-level programming language platforms (for example MATLAB, LabVIEW and Python) and/or integrated within low-level language (for example C# and C++) applications. The use of the toolbox can speed up the development and the robust integration of new robotic NDT systems with real-time adaptive capabilities and is compatible with all KUKA robots with six degrees of freedom (DOF), which are equipped with the Robot Sensor Interface (RSI) software add-on. The paper describes the architecture of the toolbox and shows two application examples, where performance results are provided. The concepts described in the paper are aligned with the emerging Industry 4.0 paradigms and have wider applicability beyond NDT

Robotic path planning for non-destructive testing - a custom MATLAB toolbox approach

The requirement to increase inspection speeds for non-destructive testing (NDT) of composite aerospace parts is common to many manufacturers. The prevalence of complex curved surfaces in the industry provides motivation for the use of 6 axis robots in these inspections. The purpose of this paper is to present work undertaken for the development of a KUKA robot manipulator based automated NDT system. A new software solution is presented that enables flexible trajectory planning to be accomplished for the inspection of complex curved surfaces often encountered in engineering production. The techniques and issues associated with conventional manual inspection techniques and automated systems for the inspection of large complex surfaces were reviewed. This approach has directly influenced the development of a MATLAB toolbox targeted to NDT automation, capable of complex path planning, obstacle avoidance, and external synchronization between robots and associated external NDT systems. This paper highlights the advantages of this software over conventional off-line-programming approaches when applied to NDT measurements. An experimental validation of path trajectory generation, on a large and curved composite aerofoil component, is presented. Comparative metrology experiments were undertaken to evaluate the real path accuracy of the toolbox when inspecting a curved 0.5 m2 and a 1.6 m2 surface using a KUKA KR16 L6-2 robot. The results have shown that the deviation of the distance between the commanded TCPs and the feedback positions were within 2.7 mm. The variance of the standoff between the probe and the scanned surfaces was smaller than the variance obtainable via commercial path-planning software. Tool paths were generated directly on the triangular mesh imported from the CAD models of the inspected components without need for an approximating analytical surface. By implementing full external control of the robotic hardware, it has been possible to synchronise the NDT data collection with positions at all points along the path, and our approach allows for the future development of additional functionality that is specific to NDT inspection problems. For the current NDT application, the deviations from CAD design and the requirements for both coarse and fine inspections, dependent on measured NDT data, demand flexibility in path planning beyond what is currently available from existing off-line robot programming software

SIMULATION AND EXPERIMENTAL WORK OF KINEMATIC PROBLEMS FOR KUKA KR 5 SIXX R650 ARTICULATED ROBOT

This paper studies an analytic solution for 6-DOF manipulator of a KUKA KR 5 SIXX R650 robotic arm using forward and inverse kinematics in a simple movement process. This paper proposes two points of movement in order to study three types of path motion used in the robotic arm. The three path motions are PTP (point-to-point), linear and circular. The motions are analyzed systemically using forward kinematics and inverse kinematics. The objective of forward kinematic analysis is to determine the cumulative effect of the entire set of joint variables. A simulation oriented analysis is obtained and comparison between simulation and experimental result is done. The result for both simulation and experimental works show close connection for the task. This robot is suitable to be applied to the teaching and training environment

El controlador KUKA youBot

En nuestros días, muchas placas base y PCBs presentan fallos debido al fin de su vida útil o a errores en el proceso de producción. En muchos de estos casos, su clasificación se realiza mediante operaciones manuales, llevando a los empleados a una posible exposición a elementos tóxicos. Debido a ello, este proyecto se propone detectar dichos fallos con el procesamiento de imágenes tomadas por una cámara Siemens MV440 mediante el programa GNU Octave, así como la clasificación de las mismas gracias a la programación de un robotbrazo KUKA youBot dentro del entorno Linux conocido Robot Operating System o ROS. Previa a la programación de dicho robot, se simulará su comportamiento dentro del programa Gazebo.Vilnius Gediminas Technical University. Faculty of Electronics. Department of Electrical EngineeringGrado en Ingeniería en Electrónica Industrial y Automátic

APPLICATION OF SIMULATION MODELS FOR PROGRAMMING OF ROBOTS

In recent years, there has been an increasing robotization of many areas of life. This requires knowledge of issues related to robots and their programming. Devices of this type, especially large industrial or medical robots, are very expensive, or they may be hardly affordable for educational purposes. Simulation models are helpful in such situation. The aim of the article is to present the possibilities of using simulation models of robots and robotic stations in the educational and research process. Specialized software packages make it easier not only to understand how robots work, but they also allow to test different operating conditions of the designed computer model of the real robotized process