1,185 research outputs found

    Minimising vibration in a flexible golf club during robotic simulations of a golf swing

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    Robots are widely used as substitutes for humans in situations involving repetitive tasks where a precise and repeatable motion is required. Sports technology is an area which has seen an increase in the implementation of robots which simulate specific human motions required for a sport. One purpose is to test sports equipment, where the requirement is for a motion to be performed with consistent variables. One issue which has arisen frequently in the robot simulation of humans is the inherent presence of vibration excited in a flexible object being manipulated by a robot, and this issue is not unfounded in the situation presented in this research, of a golf robot manipulating a flexible golf club during the simulation of a golf swing. It had been found that during robotic simulations of golf swings performed with the Miyamae Robo V at the Sports Technology Institute at Loughborough University, swing variables such as shaft deformation and clubhead orientation were dissimilar to those measured for human golf swings. Vibrations present in the golf club were identified as the key cause of the disparity between human and robot swing variables. This research sought to address this issue and find a method which could be applied to reduce clubhead vibrations present in robot simulations of a golf swing to improve their similarity to human swings. This would facilitate the use of the golf robot for equipment testing and club fitting. Golf swing variables were studied and measured for 14 human subjects with the aim being to understand the motion that the robot is required to simulate. A vibration damping gripper was then fitted to the robot to test the effect that changing the interface between the robot-excited vibrations and the club would have, this was achieved with a selection of silicone sleeves with differing material properties which could be attached to the club. Preliminary results showed a noticeable reduction in clubhead vibrations and this solution was investigated further. Mathematically modelling the robot was seen as the most suitable method for this as it meant the robot remained functional and allowed a number of solutions to be tested. Several iterations of a mathematical model were developed with the final model being structurally similar to the robot with the addition of a compliant grip and wrist. The method by which the robot is driven was also recognised as having a large effect on the level of vibration excited in the clubhead and the methodology behind generating smooth robot swing profiles is presented. The mathematical model was used to perform 6 swings and the resulting shaft deformation and clubhead vibration were compared with data from human swings. It was found that the model was capable of producing swing variables comparable to human swings, however in the downswing portion of the swing the magnitude of these variables were larger for the simulations. Simulations were made which sought to demonstrate the difference between the model replicating the rigid robot and a compliant system. Reductions in vibration were achieved in all swings, including those driven with robot feedback data which contains oscillations excited by the method with which the robot is driven

    Development and evaluation of new control algorithms for a mechanical golf swing device

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    Golf swing machines have become fundamental tools in the development of new equipment because they provide more consistent swing motions than golfers. Golf robots perform a simplification of the complex sequence of motions that compose a golf swing; however, traditional devices are typically capable of performing only a single swing profile at variable speeds. Significant differences exist between individual golfers’ swing motions, especially for golfers of different ability, experience, and physical stature, which suggests a requirement for swing profile variability in mechanical simulators. This investigation has found that the swing motion of a traditional golf robot provides a poor representation of golfers’ swings and, as a result, a bespoke control system has been developed for a commercially available golf robot to enable performance of variable swing profiles with positional feedback. Robot swing command files are generated by fitting a curve to a number of discrete data points that are equally spaced in time, and which define angles representative of individual golfers’ swings. The swing profiles of a professional golfer and a traditional golf robot were repeated accurately using this golf robot with a modified motion control system. The capability for individual golfers’ swings to be accurately replicated using a mechanical device was demonstrated using feedback data. All manufacturers recognize the importance of tailoring equipment to the unique characteristics of a particular golfer’s swing, and this increased robot functionality will provide considerable benefits in the development of customized equipment

    Implications of Rigid Gripping Constraints on Clubhead Dynamics in Steel Golf Shafts

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    Research and equipment testing with golf robots offers much greater control and manipulation of experimental variables compared to tests using human golfers. However, whilst it is acknowledged that the club gripping mechanism of a robot is dissimilar to that of a human, there appears to be no scientific findings on the effects of these gripping differences on the clubhead at ball impact. Theoretical and experimental strain propagation rates from the clubhead to the grip and back to the clubhead were determined during robot testing with a 9-iron to determine if this time interval was sufficiently short to permit the gripping mechanism to have an effect on the clubhead during impact. Longitudinal strain appears to propagate the most quickly, but such deflections are likely to be small and therefore of little meaningful consequence. Shaft bending was not a primary concern as modes of large enough amplitude appear to propagate too slowly to be relevant. Torsional strain propagates at a rate which suggests that constraints at the grip end of a golf club could potentially influence impact dynamics for steel shafted irons; however, this effect seems unlikely to be significant, a likelihood that decreases further for longer irons. As such, it is considered reasonable to treat the influence of a robot’s gripping mechanism on clubhead dynamics at impact as negligible, and therefore comparisons between robot and human data in this regard are valid

    Bidirektionale Interaktion von Mensch und Roboter beim Bewegungslernen - Visuelle Wahrnehmung von Roboterbewegungen

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    In den vergangenen Jahrzehnten haben sich die Arbeitsbereiche von Menschen und Robotern zunehmend gegenseitig durchdrungen. Interaktionen zwischen Mensch und Roboter sind in vielen Lebensbereichen, z. B. Industrie, Medizin, Rehabilitation und Sport gegenwärtig. Während Roboter bisher vorwiegend starr programmiert wurden, hat sich in den letzten Jahren ein Paradigmenwechsel hin zu einer anpassungsfähigen, lernenden Programmierung vollzogen. Basierend auf diesem neuen Ansatz der Programmierung tritt eine direkte, teils physische Interaktion zwischen Mensch und Roboter zunehmend in den Fokus der Entwicklung und eröffnet ein bisher ungeahntes Potential zur Weiterentwicklung der Mensch-Roboter-Interaktion. Die Beziehung von Mensch und Roboter ist von vielen, teils extremen Unterschieden zwischen den beiden Systemen gekennzeichnet (Verfügbare Sensorik, Anzahl der Freiheitsgrade, Anzahl der Muskeln/Aktuatoren sowie Integrationsgrad von Sensorik und Aktuatorik). Diese Unterschiede erweisen sich für die beiden Systeme in einem isolierten Bewegungslernprozess teils als Vor- und teils als Nachteil. Der Frage, wie sich die Vorteile der beiden Systeme in einem gemeinsamen bidirektionalen Bewegungslernprozess optimal kombinieren lassen, geht das Projekt Bidirectional Interaction between Human and Robot when learning movements nach. Im Rahmen dieses interdisziplinären Forschungsprojektes sollen die Erkenntnisse aus den Bereichen der Sportwissenschaft und der Informatik kombiniert und die wissenschaftliche Basis für ein verbessertes Mensch-Roboter-Training gelegt werden. Das Projekt unterteilt sich dabei in vier Teilbereiche: die bidirektionale Interaktion zweier Menschen, die unidirektionale Interaktion von Mensch und Roboter (zwei Richtungen) sowie die bidirektionale Interaktion von Mensch und Roboter. In dieser Dissertation werden drei Artikel zu der beschriebenen Thematik vorgestellt. Der erste Artikel beschreibt Ziele und Struktur des Forschungsprojekts sowie drei exemplarische Studien zu den ersten drei Teilbereichen des Projekts. Aufbauend auf den Erkenntnissen einer der vorgestellten Studien zur Bedeutung der Beobachtungsperspektive beim Bewegungslernen, fokussieren die beiden darauf folgenden Artikel die visuelle Wahrnehmung von Roboterbewegungen durch den Menschen. Der Beschreibung des Projekts in Zielen und Struktur schließt sich im Artikel I die Vorstellung von drei exemplarischen Untersuchungen an. Die erste Studie betrachtet die bidirektionale Interaktion in Mensch-Mensch-Dyaden. Sie verifiziert einen prototypischen, dyadischen Bewegungslernprozess und identifiziert relevante Themen, die auf Mensch-Roboter-Dyaden übertragen werden können. Zur unidirektionalen Interaktion zwischen Mensch und Roboter werden zwei Studien vorgestellt. Im Bereich des Lernens eines Roboters von einem Menschen wird eine iterative Feedbackstrategie eines Roboters beschrieben. Eine Untersuchung zur Bedeutung der Beobachtungsperspektive beim Bewegungslernen von Mensch und Roboter bearbeitet den Bereich des unidirektionalen Lernens eines Mensches von einem Roboter. Basierend auf dieser Untersuchung ergeben sich die Fragestellungen, die in den folgenden beiden Artikeln untersucht werden. Während viele Studien die Wahrnehmung von biologischen Bewegungen untersucht haben, befassen sich nur wenige Ansätze mit der Wahrnehmung von nichtbiologischen Roboterbewegungen. Um diese Lücke zu schließen, werden im Artikel II zwei aufeinander aufbauende Studien zur Wahrnehmung von Roboterputtbewegungen durch den Menschen vorgestellt. Es konnte gezeigt werden, dass eine Leistungsvorhersage der gezeigten Roboterputtbewegungen nur bei Sichtbarkeit der vollständigen Bewegung möglich sind. Insbesondere die Ausschwungphase scheint eine Vielzahl an räumlich-zeitlichen Informationen bereit zu stellen, die einen großen Einfluss auf die Leistungsvorhersage besitzen. Aufbauend auf den bisher gewonnenen Erkenntnissen wird im Artikel III eine Studie vorgestellt, die versucht, die für die Ableitung von räumlich-zeitlichen Informationen wichtigen Bewegungselemente zu identifizieren. Im Rahmen der vorgestellten Untersuchung wurden die gezeigten Roboterputtbewegungen teilweise manipuliert. Wichtige Bewegungselemente, z. B. Roboter, Schläger oder Ball, wurden ausgeblendet. Zusammenfassend betrachtet diese Dissertation die visuelle Wahrnehmung von Roboterbewegungen durch den Menschen am Beispiel der Puttbewegung im Golf. Der Hauptbeitrag dieser Arbeit sind Erkenntnisse, die in einen bidirektionalen Bewegungslernprozess von Mensch-Roboter-Dyaden überführt werden können. Aus der Arbeit ergeben sich weiterführende Forschungsansätze und Fragestellungen, die eine hohe Relevanz für die Weiterentwicklung der Interaktion von Mensch und Roboter besitzen

    Benchmarking Cerebellar Control

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    Cerebellar models have long been advocated as viable models for robot dynamics control. Building on an increasing insight in and knowledge of the biological cerebellum, many models have been greatly refined, of which some computational models have emerged with useful properties with respect to robot dynamics control. Looking at the application side, however, there is a totally different picture. Not only is there not one robot on the market which uses anything remotely connected with cerebellar control, but even in research labs most testbeds for cerebellar models are restricted to toy problems. Such applications hardly ever exceed the complexity of a 2 DoF simulated robot arm; a task which is hardly representative for the field of robotics, or relates to realistic applications. In order to bring the amalgamation of the two fields forwards, we advocate the use of a set of robotics benchmarks, on which existing and new computational cerebellar models can be comparatively tested. It is clear that the traditional approach to solve robotics dynamics loses ground with the advancing complexity of robotic structures; there is a desire for adaptive methods which can compete as traditional control methods do for traditional robots. In this paper we try to lay down the successes and problems in the fields of cerebellar modelling as well as robot dynamics control. By analyzing the common ground, a set of benchmarks is suggested which may serve as typical robot applications for cerebellar models

    Hierarchical Reinforcement Learning for Precise Soccer Shooting Skills using a Quadrupedal Robot

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    We address the problem of enabling quadrupedal robots to perform precise shooting skills in the real world using reinforcement learning. Developing algorithms to enable a legged robot to shoot a soccer ball to a given target is a challenging problem that combines robot motion control and planning into one task. To solve this problem, we need to consider the dynamics limitation and motion stability during the control of a dynamic legged robot. Moreover, we need to consider motion planning to shoot the hard-to-model deformable ball rolling on the ground with uncertain friction to a desired location. In this paper, we propose a hierarchical framework that leverages deep reinforcement learning to train (a) a robust motion control policy that can track arbitrary motions and (b) a planning policy to decide the desired kicking motion to shoot a soccer ball to a target. We deploy the proposed framework on an A1 quadrupedal robot and enable it to accurately shoot the ball to random targets in the real world.Comment: Accepted to 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022

    Tennis racket performance studies and the design of a novel test machine

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    The investigation was instigated by a growing concern from the International Tennis Federation (ITF) that the contribution of racket technology in the modem game of tennis might be changing the nature of the game by making it too fast. The serve was earmarked as the most critical stroke influencing the speed of the game, resulting in the decision to build a test machine, which would investigate racket performance under realistic serve conditions. In order to determine the design specifications for the machine the following studies were performed. [Continues.
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