A new approach of kinematic geometry for error identification and compensation of industrial robots

A new approach for kinematic calibration of industrial robots, including the kinematic pair errors and the link errors, is developed in this paper based on the kinematic invariants. In most methods of kinematic calibration, the geometric errors of the robots are considered in forms of variations of the link parameters, while the kinematic pairs are assumed ideal. Due to the errors of mating surfaces in kinematic pairs, the fixed and moving axes of revolute pairs, or the fixed and moving guidelines of prismatic pairs, are separated, which can be concisely identified as the kinematic pair errors and the link errors by means of the kinematic pair errors model, including the self-adaption fitting of a ruled surface, or the spherical image curve fitting and the striction curve fitting. The approach is applied to the kinematic calibration of a SCARA robot. The discrete motion of each kinematic pair in the robot is completely measured by a coordinate measuring machine. Based on the global kinematic properties of the measured motion, the fixed and moving axes, or guidelines, of the kinematic pairs are identified, which are invariants unrelated to the positions of the measured reference points. The kinematic model of the robot is set up using the identified axes and guidelines. The results validate the approach developed has good efficiency and accuracy. </jats:p

Geometric Parameter Identification of a 6-DOF Space Robot Using a Laser-Ranger

The geometric parameters of a space robot change with the terrible temperature change in orbit, which will cause the end-effector pose (position and orientation) error of a space robot, and so weakens its operability. With this in consideration, a new geometric parameter identification method is presented based on a laser-ranger attached to the end-effector. Then, independence of the geometric parameters is analyzed, and their identification equations are derived. With the derived identification Jacobian matrix, the optimal identification configurations are chosen according to the observability index O3. Subsequently, through simulation the geometric parameter identification of a 6-DOF space robot is implemented for these identification configurations, and the identified parameters are verified in a set of independent reference configurations. The result shows that in spite of distance measurement alone, pose accuracy of the space robot still has a greater improvement, so the identification method is practical and valid

Contribution to improving the accuracy of serial robots

The goal of the present study is to improve the accuracy of six-revolute industrial robots using calibration methods. These methods identify the values of the calibrated robot model to improve the correspondence between the real robot and the mathematical model used in its controller. The calibrated robot model adds error parameters to the nominal model, which correspond to the geometric errors of the robot as well as the stiffness behavior of the robot. The developed methods focus on using low cost measurement equipment. For instance, the first work makes a comparison between a robot calibration performed using a laser tracker and a stereo camera (MMT optique) separately. The accuracy performance is validated using a telescoping ballbar for each of the two methods. While the calibration result is the same for both methods, the price of a laser tracker is more than twice the price of a stereo camera. The method is tested using an ABB IRB120 robot, a Faro ION laser tracker, and a Creaform CTrack stereo camera to calibrate the robot. A Renishaw QC20-W ballbar is used to validate the accuracy. A novel measurement system to measure a set of poses is described in the second work. The device is an extension of a known approach using an hexapod (a Stewart-Gough platform). One fixture is attached to the robot base and the other to the robot end-effector, each having three magnetic cups. By taking six ballbar measurements at a time, it is possible to measure 144 poses of the triangular fixture attached to the robot end-effector with respect to the base fixture. The position accuracy of the device is 3.2 times the accuracy of the QC20-W ballbar: ± 0.003 mm. An absolute robot calibration using this novel 6D measurement system is performed in the third work of this thesis. The robot is calibrated in 61 configurations and the absolute position accuracy of the robot after calibration is validated with a Faro laser tracker in about 10,000 robot configurations. The mean distance error is improved from 1.062 mm to 0.400 mm in 50 million pairs of measurements throughout the complete robot workspace. To allow a comparison, the robot is also calibrated using the laser tracker and the robot accuracy validated in the same 10,000 robot configurations

Calibration of a serial robot using a laser tracker

The positioning performance of an industrial robot ABB IRB 1600-6/1.45 has been studied with a laser tracker. Performing some axis-by-axis analyses, we found that axes 2, 3 and 6 have a non-geometrical behavior. A 34-parameter model was used to represent the real robot. This error model takes into account the geometrical errors due to fabrication as well as four error parameters related to stiffness (in axes 2 and 3) and four other error parameters used to fit a second-order Fourier series to the non-linear behavior of axis 6. The Nelder-Mead non linear optimization technique was used to find the error parameters that best fit the measures acquired with the laser tracker. An algebraic solution for the inverse kinematics is not possible for the 34-parameter model. We therefore propose a numerical and iterative inverse algorithm to recalculate the robot targets into so-called fake targets. No more than three iterations are needed to accurately obtain the joint angles corresponding to a given pose of the end-effector. Similar tests to the ones proposed by the ISO 9283 norm are performed to compare the accuracy of the nominal and improved robot models. The validation of the accuracy is done with a large number of measures. For the 34-parameter model the mean / maximum position errors are reduced from 0.979 mm / 2.326 mm to 0.329 mm / 0.916 mm (verification performed with around 1000 measurements), at a 6 kg payload, for eight points on the endeffector and for the complete robot workspace (or almost complete, since we had to avoid some obstacles). Analyses were performed with the expected errors. They allow to “pre-validate” the models without having to take extra measurements. It was found that this pre-validation is very close to the real validation

Algorithm of adaptive modification of tool paths in robot manipulators based on the measurement of 3D real objects

The goal of this paper is the definition of an algorithm for adaptive modification of tool paths made by robot manipulators. The algorithm operates on three-dimensional reconstructions obtained from real objects mass-produced and subject to deformation due to manufacturing errors. The three-dimensional reconstruction is by means of hardware and software architecture analyzed in detail in this paper

Anthropocentric perspective of production before and within Industry 4.0

Abstract This paper presents a systematic literature review (SLR) of the anthropocentric perspective of production before and after (or, better, within) Industry 4.0. We identify central research clusters regarding traditional Anthropocentric Production Systems (APS) and Anthropocentric Cyber Physical Production Systems. By comparing the two perspectives, we are able to analyse new emerging paradigms in anthropocentric production caused by Industry 4.0. We further make prediction of the future role of the human operator, his needed knowledge and capabilities and how assistance systems support the Operator 4.0. Our paper gives a brief outlook of current and needed future research. It builds grounds for further scholarly discussion on the role of humans in the factory of the future

Kinematic Calibration of Parallel Kinematic Machines on the Example of the Hexapod of Simple Design

The aim of using parallel kinematic motion systems as an alternative of conventional machine tools for precision machining has raised the demands made on the accuracy of identification of the geometric parameters that are necessary for the kinematic transformation of the motion variables. The accuracy of a parallel manipulator is not only dependent upon an accurate control of its actuators but also upon a good knowledge of its geometrical characteristics. As the platform's controller determines the length of the actuators according to the nominal model, the resulted pose of the platform is inaccurate. One way to enhance platform accuracy is by kinematic calibration, a process by which the actual kinematic parameters are identified and then implemented to modify the kinematic model used by the controller. The first and most general valuation criterion for the actual calibration approaches is the relative improvement of the motion accuracy, eclipsing the other aspects to pay for it. The calibration outlay has been underestimated or even neglected for a long time. The scientific value of the calibration procedure is not only in direct proportion to the achieved accuracy, but also to the calibration effort. These demands become particularly stringent in case of the calibration of hexapods of the so-called simple design. The objectives of the here proposed new calibration procedure are based on the deficits mentioned above under the special requirements due to the circumstances of the simple design-concept. The main goals of the procedure can be summarized in obtaining the basics for an automated kinematic calibration procedure which works efficiently, quickly, effectively and possibly low-cost, all-in-one economically applied to the parallel kinematic machines. The problem will be approached systematically and taking step by step the necessary conclu-sions and measurements through: Systematical analysis of the workspace to determine the optimal measuring procedure, measurements with automated data acquisition and evaluation, simulated measurements based on the kinematic model of the structure and identifying the kinematic parameters using efficient optimization algorithms. The presented calibration has been successfully implemented and tested on the hexapod of simple design `Felix' available at the IWM, TU Dresden. The obtained results encourage the application of the procedure to other hexapod structures

Autonomous Drone Landings on an Unmanned Marine Vehicle using Deep Reinforcement Learning

This thesis describes with the integration of an Unmanned Surface Vehicle (USV) and an Unmanned Aerial Vehicle (UAV, also commonly known as drone) in a single Multi-Agent System (MAS). In marine robotics, the advantage offered by a MAS consists of exploiting the key features of a single robot to compensate for the shortcomings in the other. In this way, a USV can serve as the landing platform to alleviate the need for a UAV to be airborne for long periods time, whilst the latter can increase the overall environmental awareness thanks to the possibility to cover large portions of the prevailing environment with a camera (or more than one) mounted on it. There are numerous potential applications in which this system can be used, such as deployment in search and rescue missions, water and coastal monitoring, and reconnaissance and force protection, to name but a few. The theory developed is of a general nature. The landing manoeuvre has been accomplished mainly identifying, through artificial vision techniques, a fiducial marker placed on a flat surface serving as a landing platform. The raison d'etre for the thesis was to propose a new solution for autonomous landing that relies solely on onboard sensors and with minimum or no communications between the vehicles. To this end, initial work solved the problem while using only data from the cameras mounted on the in-flight drone. In the situation in which the tracking of the marker is interrupted, the current position of the USV is estimated and integrated into the control commands. The limitations of classic control theory used in this approached suggested the need for a new solution that empowered the flexibility of intelligent methods, such as fuzzy logic or artificial neural networks. The recent achievements obtained by deep reinforcement learning (DRL) techniques in end-to-end control in playing the Atari video-games suite represented a fascinating while challenging new way to see and address the landing problem. Therefore, novel architectures were designed for approximating the action-value function of a Q-learning algorithm and used to map raw input observation to high-level navigation actions. In this way, the UAV learnt how to land from high latitude without any human supervision, using only low-resolution grey-scale images and with a level of accuracy and robustness. Both the approaches have been implemented on a simulated test-bed based on Gazebo simulator and the model of the Parrot AR-Drone. The solution based on DRL was further verified experimentally using the Parrot Bebop 2 in a series of trials. The outcomes demonstrate that both these innovative methods are both feasible and practicable, not only in an outdoor marine scenario but also in indoor ones as well

The Poetry of Prompts: The Collaborative Role of Generative Artificial Intelligence in the Creation of Poetry and the Anxiety of Machine Influence

2022 has been heralded as the year of generative artificial intelligence (AI). Generative AI like ChatGPT and Stable Diffusion, along with a host of others, launched late in the year and immediately disrupted the status quo of the literary and art worlds, leading to outcries to ban “AI Art” and spawning an entirely new market of NFTs. Fears over the “death of the artist” and the “death of college composition,” however, are unfounded when considering the historical adoption of emerging technologies by creatives and the reconsideration of authorship that began with post structuralism and the Foucauldian Death of the Author in 1967. Contemporary scholarship has faced challenges in reconciling the function of the human author in conjunction with artificial intelligence (AI) due to the progressive sophistication and selfsufficiency of generative code. Nonetheless, it is erroneous to establish the threshold for authorship based on the development or advancement of AI or robotics, as it falls within the realm of ontology. Instead, assertions of AI authorship stem from a romanticized perception of both authorship and AI during a period in which neither holds significance. A new discussion on the role of the human agent in the writing process, particularly in the creative process like poetry, should prioritize the practical aspects of what an author does. This study examines how AI is increasingly becoming involved in collaborative efforts to create poetry and aims to explore the potential of this trend. Furthermore, the study seeks to provide empirical evidence on the boundaries of AI\u27s ability to replicate human thought and experience. Through generating content in the creative written arts using ChatGPT-3, poetry analysis revealed that, in fact, such new generative models can imitate the vocabulary, language choices, style, and even rhythm of famous poets such as Keats, it is unable to generate emotions that it has not experienced. The questions that will continue to be raised on the nature of humanity, existence, and creative capabilities should be reframed with the concept of fear fore grounded to assist in understanding the uniquely human anxiety and drive to create in an attempt to communicate across the gulf what it “feels” like to be human as a phenomenology of experience