909 research outputs found

    A General Framework for Hierarchical Redundancy Resolution Under Arbitrary Constraints

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    The increasing interest in autonomous robots with a high number of degrees of freedom for industrial applications and service robotics demands control algorithms to handle multiple tasks as well as hard constraints efficiently. This paper presents a general framework in which both kinematic (velocity- or acceleration-based) and dynamic (torque-based) control of redundant robots are handled in a unified fashion. The framework allows for the specification of redundancy resolution problems featuring a hierarchy of arbitrary (equality and inequality) constraints, arbitrary weighting of the control effort in the cost function and an additional input used to optimize possibly remaining redundancy. To solve such problems, a generalization of the Saturation in the Null Space (SNS) algorithm is introduced, which extends the original method according to the features required by our general control framework. Variants of the developed algorithm are presented, which ensure both efficient computation and optimality of the solution. Experiments on a KUKA LBRiiwa robotic arm, as well as simulations with a highly redundant mobile manipulator are reported.Comment: 19 pages, 19 figures, submitted to the IEE

    Advanced Strategies for Robot Manipulators

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    Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

    AI based Robot Safe Learning and Control

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    Introduction This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authorsโ€™ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities

    A Contribution to the Design of Highly Redundant Compliant Aerial Manipulation Systems

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    Es ist vorhersehbar, dass die Luftmanipulatoren in den nรคchsten Jahrzehnten fรผr viele Aufgaben eingesetzt werden, die entweder zu gefรคhrlich oder zu teuer sind, um sie mit herkรถmmlichen Methoden zu bewรคltigen. In dieser Arbeit wird eine neuartige Lรถsung fรผr die Gesamtsteuerung von hochredundanten Luftmanipulationssystemen vorgestellt. Die Ergebnisse werden auf eine Referenzkonfiguration angewendet, die als universelle Plattform fรผr die Durchfรผhrung verschiedener Luftmanipulationsaufgaben etabliert wird. Diese Plattform besteht aus einer omnidirektionalen Drohne und einem seriellen Manipulator. Um den modularen Regelungsentwurf zu gewรคhrleisten, werden zwei rechnerisch effiziente Algorithmen untersucht, um den virtuellen Eingang den Aktuatorbefehlen zuzuordnen. Durch die Integration eines auf einem kรผnstlichen neuronalen Netz basierenden Diagnosemoduls und der rekonfigurierbaren Steuerungszuordnung in den Regelkreis, wird die Fehlertoleranz fรผr die Drohne erzielt. AuรŸerdem wird die Motorsรคttigung durch Rekonfiguration der Geschwindigkeits- und Beschleunigungsprofile behandelt. Fรผr die Beobachtung der externen Krรคfte und Drehmomente werden zwei Filter vorgestellt. Dies ist notwendig, um ein nachgiebiges Verhalten des Endeffektors durch die achsenselektive Impedanzregelung zu erreichen. Unter Ausnutzung der Redundanz des vorgestellten Luftmanipulators wird ein Regler entworfen, der nicht nur die Referenz der Endeffektor-Bewegung verfolgt, sondern auch priorisierte sekundรคre Aufgaben ausfรผhrt. Die Wirksamkeit der vorgestellten Lรถsungen wird durch umfangreiche Tests รผberprรผft, und das vorgestellte Steuerungssystem wird als sehr vielseitig und effektiv bewertet.:1 Introduction 2 Fundamentals 3 System Design and Modeling 4 Reconfigurable Control Allocation 5 Fault Diagnostics For Free Flight 6 Force and Torque Observer 7 Trajectory Generation 8 Hybrid Task Priority Control 9 System Integration and Performance Evaluation 10 ConclusionIn the following decades, aerial manipulators are expected to be deployed in scenarios that are either too dangerous for human beings or too expensive to be accomplished by traditional methods. This thesis presents a novel solution for the overall control of highly redundant aerial manipulation systems. The results are applied to a reference configuration established as a universal platform for performing various aerial manipulation tasks. The platform consists of an omnidirectional multirotor UAV and a serial manipulator. To ensure modular control design, two computationally efficient algorithms are studied to allocate the virtual input to actuator commands. Fault tolerance of the aerial vehicle is achieved by integrating a diagnostic module based on an artificial neural network and the reconfigurable control allocation into the control loop. Besides, the risk of input saturation of individual rotors is minimized by predicting and reconfiguring the speed and acceleration responses. Two filter-based observers are presented to provide the knowledge of external forces and torques, which is necessary to achieve compliant behavior of the end-effector through an axis-selective impedance control in the outer loop. Exploiting the redundancy of the proposed aerial manipulator, the author has designed a control law to achieve the desired end-effector motion and execute secondary tasks in order of priority. The effectiveness of the proposed designs is verified with extensive tests generated by following Monte Carlo method, and the presented control scheme is proved to be versatile and effective.:1 Introduction 2 Fundamentals 3 System Design and Modeling 4 Reconfigurable Control Allocation 5 Fault Diagnostics For Free Flight 6 Force and Torque Observer 7 Trajectory Generation 8 Hybrid Task Priority Control 9 System Integration and Performance Evaluation 10 Conclusio

    Robot Manipulators

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    Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

    ์•ˆ์ „ํ•œ ์žฌ๊ตฌ์„ฑ ๋กœ๋ด‡ ์‹œ์Šคํ…œ: ์„ค๊ณ„, ํ”„๋กœ๊ทธ๋ž˜๋ฐ ๋ฐ ๋ฐ˜์‘ํ˜• ๊ฒฝ๋กœ๊ณ„ํš

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€, 2020. 8. ๋ฐ•์ข…์šฐ.The next generation of robots are being asked to work in close proximity to humans. At the same time, the robot should have the ability to change its topology to flexibly cope with various tasks. To satisfy these two requirements, we propose a novel modular reconfi gurable robot and accompanying software architecture, together with real-time motion planning algorithms to allow for safe operation in unstructured dynamic environments with humans. Two of the key innovations behind our modular manipulator design are a genderless connector and multi-dof modules. By making the modules connectable regardless of the input/output directions, a genderless connector increases the number of possible connections. The developed genderless connector can transmit as much load as necessary to an industrial robot. In designing two-dof modules, an offset between two joints is imposed to improve the overall integration and the safety of the modules. To cope with the complexity in modeling due to the genderless connector and multi-dof modules, a programming architecture for modular robots is proposed. The key feature of the proposed architecture is that it efficiently represents connections of multi-dof modules only with connections between modules, while existing architectures should explicitly represent all connections between links and joints. The data structure of the proposed architecture contains properties of tree-structured multi-dof modules with intra-module relations. Using the data structure and connection relations between modules, kinematic/dynamic parameters of connected modules can be obtained through forward recursion. For safe operation of modular robots, real-time robust collision avoidance algorithms for kinematic singularities are proposed. The main idea behind the algorithms is generating control inputs that increase the directional manipulability of the robot to the object direction by reducing directional safety measures. While existing directional safety measures show undesirable behaviors in the vicinity of the kinematic singularities, the proposed geometric safety measure generates stable control inputs in the entire joint space. By adding the preparatory input from the geometric safety measure to the repulsive input, a hierarchical collision avoidance algorithm that is robust to kinematic singularity is implemented. To mathematically guarantee the safety of the robot, another collision avoidance algorithm using the invariance control framework with velocity-dependent safety constraints is proposed. When the object approached the robot from a singular direction, the safety constraints are not satis ed in the initial state of the robot and the safety cannot be guaranteed using the invariance control. By proposing a control algorithm that quickly decreases the preparatory constraints below thresholds, the robot re-enters the constraint set and avoids collisions using the invariance control framework. The modularity and safety of the developed reconfi gurable robot is validated using a set of simulations and hardware experiments. The kinematic/dynamic model of the assembled robot is obtained in real-time and used to accurately control the robot. Due to the safe design of modules with o sets and the high-level safety functions with collision avoidance algorithms, the developed recon figurable robot has a broader safe workspace and wider ranger of safe operation speed than those of cooperative robots.๋‹ค์Œ ์„ธ๋Œ€์˜ ๋กœ๋ด‡์€ ์‚ฌ๋žŒ๊ณผ ๊ฐ€๊นŒ์ด์—์„œ ํ˜‘์—…ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ๋Šฅ์„ ๊ฐ€์ ธ์•ผํ•œ๋‹ค. ๊ทธ์™€ ๋™์‹œ์—, ๋กœ๋ด‡์€ ๋‹ค์–‘ํ•˜๊ฒŒ ๋ณ€ํ•˜๋Š” ์ž‘์—…์— ๋Œ€ํ•ด ์œ ์—ฐํ•˜๊ฒŒ ๋Œ€์ฒ˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ž์‹ ์˜ ๊ตฌ์กฐ๋ฅผ ๋ฐ”๊พธ๋Š” ๊ธฐ๋Šฅ์„ ๊ฐ€์ ธ์•ผ ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ๋‘ ๊ฐ€์ง€ ์š”๊ตฌ์กฐ๊ฑด์„ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•ด, ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ƒˆ๋กœ์šด ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡ ์‹œ์Šคํ…œ๊ณผ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์•„ํ‚คํ…์ณ๋ฅผ ์ œ์‹œํ•˜๊ณ , ์‚ฌ๋žŒ์ด ์กด์žฌํ•˜๋Š” ๋™์  ํ™˜๊ฒฝ์—์„œ ์•ˆ์ „ํ•œ ๋กœ๋ด‡์˜ ์šด์šฉ์„ ์œ„ํ•œ ์‹ค์‹œํ•œ ๊ฒฝ๋กœ ๊ณ„ํš ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์‹œํ•œ๋‹ค. ๊ฐœ๋ฐœ๋œ ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡์˜ ๋‘ ๊ฐ€์ง€ ํ•ต์‹ฌ์ ์ธ ํ˜์‹ ์„ฑ์€ ๋ฌด์„ฑ๋ณ„ ์ปค๋„ฅํ„ฐ์™€ ๋‹ค์ž์œ ๋„ ๋ชจ๋“ˆ์—์„œ ์ฐพ์„ ์ˆ˜ ์žˆ๋‹ค. ์ž…๋ ฅ/์ถœ๋ ฅ ๋ฐฉํ–ฅ์— ์ƒ๊ด€ ์—†์ด ๋ชจ๋“ˆ์ด ์—ฐ๊ฒฐ๋  ์ˆ˜ ์žˆ๋„๋ก ํ•จ์œผ๋กœ์จ, ๋ฌด์„ฑ๋ณ„ ์ปค๋„ฅํ„ฐ๋Š” ๊ฒฐํ•ฉ ๊ฐ€๋Šฅํ•œ ๊ฒฝ์šฐ์˜ ์ˆ˜๋ฅผ ๋Š˜๋ฆด ์ˆ˜ ์žˆ๋‹ค. ๊ฐœ๋ฐœ๋œ ๋ฌด์„ฑ๋ณ„ ์ปค๋„ฅํ„ฐ๋Š” ์‚ฐ์—…์šฉ ๋กœ๋ด‡์—์„œ ์š”๊ตฌ๋˜๋Š” ์ถฉ๋ถ„ํ•œ ๋ถ€ํ•˜๋ฅผ ๊ฒฌ๋”œ ์ˆ˜ ์žˆ๋„๋ก ์„ค๊ณ„๋˜์—ˆ๋‹ค. 2 ์ž์œ ๋„ ๋ชจ๋“ˆ์˜ ์„ค๊ณ„์—์„œ ๋‘ ์ถ• ์‚ฌ์ด์— ์˜คํ”„์…‹์„ ๊ฐ€์ง€๋„๋ก ํ•จ์œผ๋กœ์จ ์ „์ฒด์ ์ธ ์™„์„ฑ๋„ ๋ฐ ์•ˆ์ „๋„๋ฅผ ์ฆ๊ฐ€์‹œ์ผฐ๋‹ค. ๋ฌด์„ฑ๋ณ„ ์ปค๋„ฅํ„ฐ์™€ ๋‹ค์ž์œ ๋„ ๋ชจ๋“ˆ๋กœ ์ธํ•œ ๋ชจ๋ธ๋ง์˜ ๋ณต์žก์„ฑ์— ๋Œ€์‘ํ•˜๊ธฐ ์œ„ํ•ด, ์ผ๋ฐ˜์ ์ธ ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡์„ ์œ„ํ•œ ์†Œํ”„ํŠธ์›จ์–ด ์•„ํ‚คํ…์ณ๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค. ๊ธฐ์กด ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡์˜ ์—ฐ๊ฒฐ์„ ๋‚˜ํƒ€๋‚ด๋Š” ๋ฐฉ๋ฒ•์ด ๋ชจ๋“  ๋งํฌ์™€ ์กฐ์ธํŠธ ์‚ฌ์ด์˜ ์—ฐ๊ฒฐ ๊ด€๊ณ„๋ฅผ ๋ณ„๋„๋กœ ๋‚˜ํƒ€๋‚ด์•ผํ•˜๋Š” ๊ฒƒ๊ณผ ๋‹ค๋ฅด๊ฒŒ, ์ œ์•ˆ๋œ ์•„ํ‚คํ…์ณ๋Š” ๋ชจ๋“ˆ๋“ค ์‚ฌ์ด์˜ ์—ฐ๊ฒฐ๊ด€๊ณ„๋งŒ์„ ๋‚˜ํƒ€๋ƒ„์œผ๋กœ์จ ํšจ์œจ์ ์ธ ๋‹ค์ž์œ ๋„ ๋ชจ๋“ˆ์˜ ์—ฐ๊ฒฐ๊ด€๊ณ„๋ฅผ ๋‚˜ํƒ€๋‚ผ ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ํŠน์ง•์œผ๋กœ ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ํŠธ๋ฆฌ ๊ตฌ์กฐ๋ฅผ ๊ฐ€์ง€๋Š” ์ผ๋ฐ˜์ ์ธ ๋‹ค์ž์œ ๋„ ๋ชจ๋“ˆ์˜ ์„ฑ์งˆ์„ ๋‚˜ํƒ€๋‚ด๋Š” ๋ฐ์ดํ„ฐ ๊ตฌ์กฐ๋ฅผ ์ •์˜ํ•˜์˜€๋‹ค. ๋ชจ๋“ˆ๋“ค ์‚ฌ์ด์˜ ์—ฐ๊ฒฐ๊ด€๊ณ„ ๋ฐ ๋ฐ์ดํ„ฐ ๊ตฌ์กฐ๋ฅผ ์ด์šฉํ•˜์—ฌ, ์ •ํ™•ํ•œ ๊ธฐ๊ตฌํ•™/๋™์—ญํ•™ ๋ชจ๋ธ ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ์–ป์–ด๋‚ด๋Š” ์ˆœ๋ฐฉํ–ฅ ์žฌ๊ท€ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ˜„ํ•˜์˜€๋‹ค. ๋ชจ๋“ˆ๋ผ ๋กœ๋ด‡์˜ ์•ˆ์ „ํ•œ ์šด์šฉ์„ ์œ„ํ•ด, ๊ธฐ๊ตฌํ•™์  ํŠน์ด์ ์— ๊ฐ•๊ฑดํ•œ ์‹ค์‹œ๊ฐ„ ์ถฉ๋ŒํšŒํ”ผ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋ฐฉํ–ฅ์„ฑ ์•ˆ์ „๋„๋ฅผ ์ค„์ด๋Š” ๋ฐฉํ–ฅ์˜ ์ œ์–ด ์ž…๋ ฅ์„ ์ƒ์„ฑํ•˜์—ฌ ๋ฌผ์ฒด ๋ฐฉํ–ฅ์œผ๋กœ์˜ ๋กœ๋ด‡ ๋ฐฉํ–ฅ์„ฑ ๋งค๋‹ˆํ“ฐ๋Ÿฌ๋นŒ๋ฆฌํ‹ฐ๋ฅผ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ๊ฒƒ์ด ์ œ์•ˆํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์˜ ํ•ต์‹ฌ์ด๋‹ค. ๊ธฐ์กด์˜ ๋ฐฉํ–ฅ์„ฑ ์•ˆ์ „๋„๊ฐ€ ๊ธฐ๊ตฌํ•™์  ํŠน์ด์  ๊ทผ์ฒ˜์—์„œ ์›ํ•˜์ง€ ์•Š๋Š” ์„ฑ์งˆ์„ ๊ฐ€์ง€๋Š” ๊ฒƒ๊ณผ๋Š” ๋ฐ˜๋Œ€๋กœ, ์ œ์•ˆํ•œ ๊ธฐํ•˜ํ•™์  ์•ˆ์ „๋„๋Š” ์ „์ฒด ์กฐ์ธํŠธ ๊ณต๊ฐ„์—์„œ ์•ˆ์ •์ ์ธ ์ œ์–ด ์ž…๋ ฅ์„ ์ƒ์„ฑํ•œ๋‹ค. ์ด ๊ธฐํ•˜ํ•™์  ์•ˆ์ „๋„๋ฅผ ์ด์šฉํ•˜์—ฌ, ๊ธฐ๊ตฌํ•™์  ํŠน์ด์ ์— ๊ฐ•๊ฑดํ•œ ๊ณ„์ธต์  ์ถฉ๋ŒํšŒํ”ผ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ๊ตฌํ˜„ํ•˜์˜€๋‹ค. ์ˆ˜ํ•™์ ์œผ๋กœ ๋กœ๋ด‡์˜ ์•ˆ์ „๋„๋ฅผ ๋ณด์žฅํ•˜๊ธฐ ์œ„ํ•ด, ์ƒ๋Œ€์†๋„์— ์ข…์†์ ์ธ ์•ˆ์ „ ์ œ์•ฝ์กฐ๊ฑด์„ ๊ฐ€์ง€๋Š” ๋ถˆ๋ณ€ ์ œ์–ด ํ”„๋ ˆ์ž„์›Œํฌ์„ ์ด์šฉํ•˜์—ฌ ๋˜ ํ•˜๋‚˜์˜ ์ถฉ๋Œ ํšŒํ”ผ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๋ฌผ์ฒด๊ฐ€ ํŠน์ด์  ๋ฐฉํ–ฅ์œผ๋กœ๋ถ€ํ„ฐ ๋กœ๋ด‡์— ์ ‘๊ทผํ•  ๋•Œ, ๋กœ๋ด‡์˜ ์ดˆ๊ธฐ ์ƒํƒœ์—์„œ ์•ˆ์ „ ์ œ์•ฝ์กฐ๊ฑด์„ ๋งŒ์กฑ์‹œํ‚ค์ง€ ๋ชปํ•˜๊ฒŒ ๋˜์–ด ๋ถˆ๋ณ€์ œ์–ด๋ฅผ ์ ์šฉํ•  ์ˆ˜ ์—†๊ฒŒ ๋œ๋‹ค. ์ค€๋น„ ์ œ์•ฝ์กฐ๊ฑด์„ ๋น ๋ฅด๊ฒŒ ์ž„๊ณ„์  ์•„๋ž˜๋กœ ๊ฐ์†Œ์‹œํ‚ค๋Š” ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ ์šฉํ•จ์œผ๋กœ์จ, ๋กœ๋ด‡์€ ์ œ์•ฝ์กฐ๊ฑด ์ง‘ํ•ฉ์— ๋‹ค์‹œ ๋“ค์–ด๊ฐ€๊ณ  ๋ถˆ๋ณ€ ์ œ์–ด ๋ฐฉ๋ฒ•์„ ์ด์šฉํ•˜์—ฌ ์ถฉ๋Œ์„ ํšŒํ”ผํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋œ๋‹ค. ๊ฐœ๋ฐœ๋œ ์žฌ๊ตฌ์„ฑ ๋กœ๋ด‡์˜ ๋ชจ๋“ˆ๋ผ๋ฆฌํ‹ฐ์™€ ์•ˆ์ „๋„๋Š” ์ผ๋ จ์˜ ์‹œ๋ฎฌ๋ ˆ์ด์…˜๊ณผ ํ•˜๋“œ์›จ์–ด ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆ๋˜์—ˆ๋‹ค. ์‹ค์‹œ๊ฐ„์œผ๋กœ ์กฐ๋ฆฝ๋œ ๋กœ๋ด‡์˜ ๊ธฐ๊ตฌํ•™/๋™์—ญํ•™ ๋ชจ๋ธ์„ ์–ป์–ด๋‚ด ์ •๋ฐ€ ์ œ์–ด์— ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์•ˆ์ „ํ•œ ๋ชจ๋“ˆ ๋””์ž์ธ๊ณผ ์ถฉ๋Œ ํšŒํ”ผ ๋“ฑ์˜ ๊ณ ์ฐจ์› ์•ˆ์ „ ๊ธฐ๋Šฅ์„ ํ†ตํ•˜์—ฌ, ๊ฐœ๋ฐœ๋œ ์žฌ๊ตฌ์„ฑ ๋กœ๋ด‡์€ ๊ธฐ์กด ํ˜‘๋™๋กœ๋ด‡๋ณด๋‹ค ๋„“์€ ์•ˆ์ „ํ•œ ์ž‘์—…๊ณต๊ฐ„๊ณผ ์ž‘์—…์†๋„๋ฅผ ๊ฐ€์ง„๋‹ค.1 Introduction 1 1.1 Modularity and Recon gurability 1 1.2 Safe Interaction 4 1.3 Contributions of This Thesis 9 1.3.1 A Recon gurable Modular Robot System with Bidirectional Modules 9 1.3.2 A Modular Robot Software Programming Architecture 10 1.3.3 Anticipatory Collision Avoidance Planning 11 1.4 Organization of This Thesis 14 2 Design and Prototyping of the ModMan 17 2.1 Genderless Connector 18 2.2 Modules for ModMan 21 2.2.1 Joint Modules 21 2.2.2 Link and Gripper Modules 25 2.3 Experiments 26 2.3.1 System Setup 26 2.3.2 Repeatability Comparison with Non-recon gurable Robot Manipulators 28 2.3.3 E ect of the O set in Two-dof Modules 30 2.4 Conclusion 32 3 A Programming Architecture for Modular Recon gurable Robots 33 3.1 Data Structure for Multi-dof Joint Modules 34 3.2 Automatic Kinematic Modeling 37 3.3 Automatic Dynamic Modeling 40 3.4 Flexibility in Manipulator 42 3.5 Experiments 45 3.5.1 System Setup 46 3.5.2 Recon gurability 46 3.5.3 Pick-and-Place with Vision Sensors 48 3.6 Conclusion 49 4 A Preparatory Safety Measure for Robust Collision Avoidance 51 4.1 Preliminaries on Manipulability and Safety 52 4.2 Analysis on Reected Mass 56 4.3 Manipulability Control on S+(1;m) 60 4.3.1 Geometry of the Group of Positive Semi-de nite Matrices 60 4.3.2 Rank-One Manipulability Control 63 4.4 Collision Avoidance with Preparatory Action 65 4.4.1 Repulsive and Preparatory Potential Functions 65 4.4.2 Hierarchical Control and Task Relaxation 67 4.5 Experiments 70 4.5.1 Manipulability Control 71 4.5.2 Collision Avoidance 75 4.6 Conclusion 82 5 Collision Avoidance with Velocity-Dependent Constraints 85 5.1 Input-Output Linearization 87 5.2 Invariance Control 89 5.3 Velocity-Dependent Constraints for Robot Safety 90 5.3.1 Velocity-Dependent Repulsive Constraints 90 5.3.2 Preparatory Constraints 92 5.3.3 Corrective Control for Dangerous Initial State 93 5.4 Experiment 95 5.5 Conclusion 98 6 Conclusion 101 6.1 Overview of This Thesis 101 6.2 Future Work 104 Appendix A Appendix 107 A.1 Preliminaries on Graph Theory 107 A.2 Lie-Theoretic Formulations of Robot Kinematics and Dynamics 108 A.3 Derivatives of Eigenvectors and Eigenvalues 110 A.4 Proof of Proposition Proposition 4.1 111 A.5 Proof of Triangle Inequality When p = 1 114 A.6 Detailed Conditions for a Danger Field 115 Bibliography 117 Abstract 127Docto

    Modeling and Control of Flexible Link Manipulators

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    Autonomous maritime navigation and offshore operations have gained wide attention with the aim of reducing operational costs and increasing reliability and safety. Offshore operations, such as wind farm inspection, sea farm cleaning, and ship mooring, could be carried out autonomously or semi-autonomously by mounting one or more long-reach robots on the ship/vessel. In addition to offshore applications, long-reach manipulators can be used in many other engineering applications such as construction automation, aerospace industry, and space research. Some applications require the design of long and slender mechanical structures, which possess some degrees of flexibility and deflections because of the material used and the length of the links. The link elasticity causes deflection leading to problems in precise position control of the end-effector. So, it is necessary to compensate for the deflection of the long-reach arm to fully utilize the long-reach lightweight flexible manipulators. This thesis aims at presenting a unified understanding of modeling, control, and application of long-reach flexible manipulators. State-of-the-art dynamic modeling techniques and control schemes of the flexible link manipulators (FLMs) are discussed along with their merits, limitations, and challenges. The kinematics and dynamics of a planar multi-link flexible manipulator are presented. The effects of robot configuration and payload on the mode shapes and eigenfrequencies of the flexible links are discussed. A method to estimate and compensate for the static deflection of the multi-link flexible manipulators under gravity is proposed and experimentally validated. The redundant degree of freedom of the planar multi-link flexible manipulator is exploited to minimize vibrations. The application of a long-reach arm in autonomous mooring operation based on sensor fusion using camera and light detection and ranging (LiDAR) data is proposed.publishedVersio
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