210 research outputs found

    An Automated Conversion Between Selected Robot Kinematic Representations

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    This paper presents a methodology that forms an automated tool for robot kinematic representation conversion, called the RobKin Interpreter. It is a set of analytical algorithms that can analyze an input robot representation, express the joints globally in matrix form, and map to other representations such as standard Denavit-Hartenberg parameters, Roll-Pitch-Yaw angles with translational displacement, and Product of Exponentials with a possibility to generate a URDF (Universal Robot Description Format) file from any of them. It works for revolute and prismatic joints and can interpret even arbitrary kinematic structures that do not have orthogonally placed joints

    Industrial Robotics

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    This book covers a wide range of topics relating to advanced industrial robotics, sensors and automation technologies. Although being highly technical and complex in nature, the papers presented in this book represent some of the latest cutting edge technologies and advancements in industrial robotics technology. This book covers topics such as networking, properties of manipulators, forward and inverse robot arm kinematics, motion path-planning, machine vision and many other practical topics too numerous to list here. The authors and editor of this book wish to inspire people, especially young ones, to get involved with robotic and mechatronic engineering technology and to develop new and exciting practical applications, perhaps using the ideas and concepts presented herein

    Task-Based Mass Optimization of Reconfigurable Robotic Manipulator Systems

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    This work develops a method for implementing task-based mass optimization of modular, reconfigurable manipulators. Link and joint modules are selected from a library of potential parts and assembled into serial manipulator configurations. A genetic algorithm is used to search over the potential set of combinations to find mass-minimized solutions. To facilitate the automatic evaluation required by the genetic algorithm, Denavit-Hartenberg parameters are automatically generated from module combinations. Reconfigurable manipulators are shown to be lighter than fixed-topology manipulators, demonstrating the potential utility of reconfigurable robotics technology for mass reduction in space robots

    Kinematics and Robot Design I, KaRD2018

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    This volume collects the papers published on the Special Issue “Kinematics and Robot Design I, KaRD2018” (https://www.mdpi.com/journal/robotics/special_issues/KARD), which is the first issue of the KaRD Special Issue series, hosted by the open access journal “MDPI Robotics”. The KaRD series aims at creating an open environment where researchers can present their works and discuss all the topics focused on the many aspects that involve kinematics in the design of robotic/automatic systems. Kinematics is so intimately related to the design of robotic/automatic systems that the admitted topics of the KaRD series practically cover all the subjects normally present in well-established international conferences on “mechanisms and robotics”. KaRD2018 received 22 papers and, after the peer-review process, accepted only 14 papers. The accepted papers cover some theoretical and many design/applicative aspects

    Advances in Robot Kinematics : Proceedings of the 15th international conference on Advances in Robot Kinematics

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    International audienceThe motion of mechanisms, kinematics, is one of the most fundamental aspect of robot design, analysis and control but is also relevant to other scientific domains such as biome- chanics, molecular biology, . . . . The series of books on Advances in Robot Kinematics (ARK) report the latest achievement in this field. ARK has a long history as the first book was published in 1991 and since then new issues have been published every 2 years. Each book is the follow-up of a single-track symposium in which the participants exchange their results and opinions in a meeting that bring together the best of world’s researchers and scientists together with young students. Since 1992 the ARK symposia have come under the patronage of the International Federation for the Promotion of Machine Science-IFToMM.This book is the 13th in the series and is the result of peer-review process intended to select the newest and most original achievements in this field. For the first time the articles of this symposium will be published in a green open-access archive to favor free dissemination of the results. However the book will also be o↵ered as a on-demand printed book.The papers proposed in this book show that robot kinematics is an exciting domain with an immense number of research challenges that go well beyond the field of robotics.The last symposium related with this book was organized by the French National Re- search Institute in Computer Science and Control Theory (INRIA) in Grasse, France

    Development of Novel Task-Based Configuration Optimization Methodologies for Modular and Reconfigurable Robots Using Multi-Solution Inverse Kinematic Algorithms

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    Modular and Reconfigurable Robots (MRRs) are those designed to address the increasing demand for flexible and versatile manipulators in manufacturing facilities. The term, modularity, indicates that they are constructed by using a limited number of interchangeable standardized modules which can be assembled in different kinematic configurations. Thereby, a wide variety of specialized robots can be built from a set of standard components. The term, reconfigurability, implies that the robots can be disassembled and rearranged to accommodate different products or tasks rather than being replaced. A set of MRR modules may consist of joints, links, and end-effectors. Different kinematic configurations are achieved by using different joint, link, and end-effector modules and by changing their relative orientation. The number of distinct kinematic configurations, attainable by a set of modules, varies with respect to the size of the module set from several tens to several thousands. Although determining the most suitable configuration for a specific task from a predefined set of modules is a highly nonlinear optimization problem in a hybrid continuous and discrete search space, a solution to this problem is crucial to effectively utilize MRRs in manufacturing facilities. The objective of this thesis is to develop novel optimization methods that can effectively search the Kinematic Configuration (KC) space to identify the most suitable manipulator for any given task. In specific terms, the goal is to develop and synthesize fast and efficient algorithms for a Task-Based Configuration Optimization (TBCO) from a given set of constraints and optimization criteria. To achieve such efficiency, a TBCO solver, based on Memetic Algorithms (MA), is proposed. MAs are hybrids of Genetic Algorithms (GAs) and local search algorithms. MAs benefit from the exploration abilities of GAs and the exploitation abilities of local search methods simultaneously. Consequently, MAs can significantly enhance the search efficiency of a wide range of optimization problems, including the TBCO. To achieve more optimal solutions, the proposed TBCO utilizes all the solutions of the Inverse Kinematics(IK) problem. Another objective is to develop a method for incorporating the multiple solutions of the IK problem in a trajectory optimization framework. The output of the proposed trajectory optimization method consists of a sequence of desired tasks and a single IK solution to reach each task point. Moreover, the total cost of the optimized trajectory is utilized in the TBCO as a performance measure, providing a means to identify kinematic configurations with more efficient optimized trajectories. The final objective is to develop novel IK solvers which are both general and complete. Generality means that the solvers are applicable to all the kinematic configurations which can be assembled from the available module inventory. Completeness entails the algorithm can obtain all the possible IK solutions

    Inverse Kinematic Analysis of Robot Manipulators

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    An important part of industrial robot manipulators is to achieve desired position and orientation of end effector or tool so as to complete the pre-specified task. To achieve the above stated goal one should have the sound knowledge of inverse kinematic problem. The problem of getting inverse kinematic solution has been on the outline of various researchers and is deliberated as thorough researched and mature problem. There are many fields of applications of robot manipulators to execute the given tasks such as material handling, pick-n-place, planetary and undersea explorations, space manipulation, and hazardous field etc. Moreover, medical field robotics catches applications in rehabilitation and surgery that involve kinematic, dynamic and control operations. Therefore, industrial robot manipulators are required to have proper knowledge of its joint variables as well as understanding of kinematic parameters. The motion of the end effector or manipulator is controlled by their joint actuator and this produces the required motion in each joints. Therefore, the controller should always supply an accurate value of joint variables analogous to the end effector position. Even though industrial robots are in the advanced stage, some of the basic problems in kinematics are still unsolved and constitute an active focus for research. Among these unsolved problems, the direct kinematics problem for parallel mechanism and inverse kinematics for serial chains constitute a decent share of research domain. The forward kinematics of robot manipulator is simpler problem and it has unique or closed form solution. The forward kinematics can be given by the conversion of joint space to Cartesian space of the manipulator. On the other hand inverse kinematics can be determined by the conversion of Cartesian space to joint space. The inverse kinematic of the robot manipulator does not provide the closed form solution. Hence, industrial manipulator can achieve a desired task or end effector position in more than one configuration. Therefore, to achieve exact solution of the joint variables has been the main concern to the researchers. A brief introduction of industrial robot manipulators, evolution and classification is presented. The basic configurations of robot manipulator are demonstrated and their benefits and drawbacks are deliberated along with the applications. The difficulties to solve forward and inverse kinematics of robot manipulator are discussed and solution of inverse kinematic is introduced through conventional methods. In order to accomplish the desired objective of the work and attain the solution of inverse kinematic problem an efficient study of the existing tools and techniques has been done. A review of literature survey and various tools used to solve inverse kinematic problem on different aspects is discussed. The various approaches of inverse kinematic solution is categorized in four sections namely structural analysis of mechanism, conventional approaches, intelligence or soft computing approaches and optimization based approaches. A portion of important and more significant literatures are thoroughly discussed and brief investigation is made on conclusions and gaps with respect to the inverse kinematic solution of industrial robot manipulators. Based on the survey of tools and techniques used for the kinematic analysis the broad objective of the present research work is presented as; to carry out the kinematic analyses of different configurations of industrial robot manipulators. The mathematical modelling of selected robot manipulator using existing tools and techniques has to be made for the comparative study of proposed method. On the other hand, development of new algorithm and their mathematical modelling for the solution of inverse kinematic problem has to be made for the analysis of quality and efficiency of the obtained solutions. Therefore, the study of appropriate tools and techniques used for the solution of inverse kinematic problems and comparison with proposed method is considered. Moreover, recommendation of the appropriate method for the solution of inverse kinematic problem is presented in the work. Apart from the forward kinematic analysis, the inverse kinematic analysis is quite complex, due to its non-linear formulations and having multiple solutions. There is no unique solution for the inverse kinematics thus necessitating application of appropriate predictive models from the soft computing domain. Artificial neural network (ANN) can be gainfully used to yield the desired results. Therefore, in the present work several models of artificial neural network (ANN) are used for the solution of the inverse kinematic problem. This model of ANN does not rely on higher mathematical formulations and are adept to solve NP-hard, non-linear and higher degree of polynomial equations. Although intelligent approaches are not new in this field but some selected models of ANN and their hybridization has been presented for the comparative evaluation of inverse kinematic. The hybridization scheme of ANN and an investigation has been made on accuracies of adopted algorithms. On the other hand, any Optimization algorithms which are capable of solving various multimodal functions can be implemented to solve the inverse kinematic problem. To overcome the problem of conventional tool and intelligent based method the optimization based approach can be implemented. In general, the optimization based approaches are more stable and often converge to the global solution. The major problem of ANN based approaches are its slow convergence and often stuck in local optimum point. Therefore, in present work different optimization based approaches are considered. The formulation of the objective function and associated constrained are discussed thoroughly. The comparison of all adopted algorithms on the basis of number of solutions, mathematical operations and computational time has been presented. The thesis concludes the summary with contributions and scope of the future research work

    Stable locomotion of humanoid robots based on mass concentrated model

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    El estudio de la locomoción de robots humanoides es actualmente un área muy activa, en el campo de la robótica. Partiendo del principio que el hombre esta construyendo robots para trabajar juntos cooperando en ambientes humanos. La estabilidad durante la caminata es un factor crítico que prevee la caída del robot, la cual puede causar deterioros al mismo y a las personas en su entorno. De esta manera, el presente trabajo pretende resolver una parte del problema de la locomoción bípeda, esto es los métodos empleados para “La generación del paso” (“Gait generation”) y asi obtener la caminata estable. Para obtener una marcha estable se utilizan modelos de masa concentrada. De esta manera el modelo del “pendulo invertido simple” y el modelo del “carro sobre la mesa” se han utilizado para conseguir la marcha estable de robots humanoides. En el modelo del pendulo invertido, la masa el pendulo conduce el movimiento del centro de gravedad (CDG) del robot humanoide durante la marcha. Se detallara que el CDG se mueve como una bola libre sobre un plano bajo las leyes del pendulo en el campo de gravedad. Mientras que en el modelo del “carro sobre la mesa”, el carro conduce el movimiento del CDG durante la marcha. En este caso, el movimiento del carro es tratado como un sistema servocontrolado, y el movimiento del CDG es obtenido con los actuales y futuros estados de referencia del Zero Moment Point (ZMP). El método para generar el paso propuesto esta compuesto de varias capas como son Movimiento global, movimiento local, generación de patrones de movimiento, cinemática inversa y dinámica inversa y finalmente una corrección off-line. Donde la entrada en este método es la meta global (es decir la configuración final del robot, en el entorno de marcha) y las salidas son los patrones de movimiento de las articulaciones junto con el patrón de referencia del ZMP. Por otro lado, se ha propuesto el método para generar el “Paso acíclico”. Este método abarca el movimiento del paso dinámico incluyendo todo el cuerpo del robot humanoide, desde desde cuaquier postura genérica estáticamente estable hasta otra; donde las entradas son los estados inicial y final del robot (esto es los ángulos iniciales y finales de las articulaciones) y las salidas son las trayectorias de referencia de cada articulación y del ZMP. Se han obtenido resultados satisfactorios en las simulaciones y en el robot humanoide real Rh-1 desarrollado en el Robotics lab de la Universidad Carlos III de Madrid. De igual manera el movimiento innovador llamado “Paso acíclico” se ha implemenado exitosamente en el robot humanoide HRP-2 (desarrollado por el AIST e Industrias Kawada Inc., Japon). Finalmente los resultados, contribuciones y trabajos futuros se expondran y discutirán. _______________________________________________The study of humanoid robot locomotion is currently a very active area in robotics, since humans build robots to work their environments in common cooperation and in harmony. Stability during walking motion is a critical fact in preventing the robot from falling down and causing the human or itself damages. This work tries to solve a part of the locomotion problem, which is, the “Gait Generation” methods used to obtain stable walking. Mass concentrated models are used to obtain stable walking motion. Thus the inverted pendulum model and the cart-table model are used to obtain stable walking motion in humanoid robots. In the inverted pendulum model, the mass of the pendulum drives the center of gravity (COG) motion of the humanoid robot while it is walking. It will be detailed that the COG moves like a free ball on a plane under the laws of the pendulum in the field of gravity. While in the cart-table model, the cart drives the COG motion during walking motion. In this case, the cart motion is treated as a servo control system, obtaining its motion from future reference states of the ZMP. The gait generation method proposed has many layers like Global motion, local motion, motion patterns generation, inverse kinematics and inverse dynamics and finally off-line correction. When the input in the gait generation method is the global goal (that is the final configuration of the robot in walking environment), and the output is the joint patterns and ZMP reference patterns. Otherwise, the “Acyclic gait” method is proposed. This method deals with the whole body humanoid robot dynamic step motion from any generic posture to another one when the input is the initial and goal robot states (that is the initial and goal joint angles) and the output is the joint and ZMP reference patterns. Successful simulation and actual results have been obtained with the Rh- 1 humanoid robot developed in the Robotics lab (Universidad Carlos III de Madrid, Spain) and the innovative motion called “Acyclic gait” implemented in the HRP-2 humanoid robot platform (developed by the AIST and Kawada Industries Inc., Japan). Furthermore, the results, contributions and future works will be discussed

    An analytic approach to converting POE parameters into D-H parameters for serial-link robots

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    The Denavit-Hartenberg (D-H) model and the product of exponentials (POE) model have been two popular methods for modeling the kinematics of a serial-link robot. While these two models are equivalent in essence, no study has revealed how to convert from the POE model to the D-H model. The conversion enables direct utilization of established algorithms formulated with D-H parameters or compensation of the D-H model after calibration with the POE parameters. It also provides a simpler method to determine the D-H parameters of a robot. For these reasons, this paper proposes an analytic approach to automatically convert a group of POE parameters into the associated D-H parameters. Three lemmas are put forward and proved to derive the final algorithm. An implementation of the algorithm in MATLAB is provided as well

    Climbing and Walking Robots

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    Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study
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