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Author: Hak Yi Publisher: ISBN: Category : Languages : en Pages : 104
Book Description
This dissertation discusses an implementation of a design, control and motion planning for a novel extendable modular redundant robotic manipulator in space constraints, which robots may encounter for completing required tasks in small and constrained environment. The design intent is to facilitate the movement of the proposed robotic manipulator in constrained environments, such as rubble piles. The proposed robotic manipulator with multi Degree of Freedom (m-DOF) links is capable of elongating by 25% of its nominal length. In this context, a design optimization problem with multiple objectives is also considered. In order to identify the benefits of the proposed design strategy, the reachable workspace of the proposed manipulator is compared with that of the Jet Propulsion Laboratory (JPL) serpentine robot. The simulation results show that the proposed manipulator has a relatively efficient reachable workspace, needed in constrained environments. The singularity and manipulability of the designed manipulator are investigated. In this study, we investigate the number of links that produces the optimal design architecture of the proposed robotic manipulator. The total number of links decided by a design optimization can be useful distinction in practice. Also, we have considered a novel robust bio-inspired Sliding Mode Control (SMC) to achieve favorable tracking performance for a class of robotic manipulators with uncertainties. To eliminate the chattering problem of the conventional sliding mode control, we apply the Brain Emotional Learning Based Intelligent Control (BELBIC) to adaptively adjust the control input law in sliding mode control. The on-line computed parameters achieve favorable system robustness in process of parameter uncertainties and external disturbances. The simulation results demonstrate that our control strategy is effective in tracking high speed trajectories with less chattering, as compared to the conventional sliding mode control. The learning process of BLS is shown to enhance the performance of a new robust controller. Lastly, we consider the potential field methodology to generate a desired trajectory in small and constrained environments. Also, Obstacle Collision Avoidance (OCA) is applied to obtain an inverse kinematic solution of a redundant robotic manipulator. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/148298
Author: Hak Yi Publisher: ISBN: Category : Languages : en Pages : 104
Book Description
This dissertation discusses an implementation of a design, control and motion planning for a novel extendable modular redundant robotic manipulator in space constraints, which robots may encounter for completing required tasks in small and constrained environment. The design intent is to facilitate the movement of the proposed robotic manipulator in constrained environments, such as rubble piles. The proposed robotic manipulator with multi Degree of Freedom (m-DOF) links is capable of elongating by 25% of its nominal length. In this context, a design optimization problem with multiple objectives is also considered. In order to identify the benefits of the proposed design strategy, the reachable workspace of the proposed manipulator is compared with that of the Jet Propulsion Laboratory (JPL) serpentine robot. The simulation results show that the proposed manipulator has a relatively efficient reachable workspace, needed in constrained environments. The singularity and manipulability of the designed manipulator are investigated. In this study, we investigate the number of links that produces the optimal design architecture of the proposed robotic manipulator. The total number of links decided by a design optimization can be useful distinction in practice. Also, we have considered a novel robust bio-inspired Sliding Mode Control (SMC) to achieve favorable tracking performance for a class of robotic manipulators with uncertainties. To eliminate the chattering problem of the conventional sliding mode control, we apply the Brain Emotional Learning Based Intelligent Control (BELBIC) to adaptively adjust the control input law in sliding mode control. The on-line computed parameters achieve favorable system robustness in process of parameter uncertainties and external disturbances. The simulation results demonstrate that our control strategy is effective in tracking high speed trajectories with less chattering, as compared to the conventional sliding mode control. The learning process of BLS is shown to enhance the performance of a new robust controller. Lastly, we consider the potential field methodology to generate a desired trajectory in small and constrained environments. Also, Obstacle Collision Avoidance (OCA) is applied to obtain an inverse kinematic solution of a redundant robotic manipulator. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/148298
Author: Yunong Zhang Publisher: Springer Science & Business Media ISBN: 3642375189 Category : Technology & Engineering Languages : en Pages : 201
Book Description
Repetitive Motion Planning and Control of Redundant Robot Manipulators presents four typical motion planning schemes based on optimization techniques, including the fundamental RMP scheme and its extensions. These schemes are unified as quadratic programs (QPs), which are solved by neural networks or numerical algorithms. The RMP schemes are demonstrated effectively by the simulation results based on various robotic models; the experiments applying the fundamental RMP scheme to a physical robot manipulator are also presented. As the schemes and the corresponding solvers presented in the book have solved the non-repetitive motion problems existing in redundant robot manipulators, it is of particular use in applying theoretical research based on the quadratic program for redundant robot manipulators in industrial situations. This book will be a valuable reference work for engineers, researchers, advanced undergraduate and graduate students in robotics fields. Yunong Zhang is a professor at The School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China; Zhijun Zhang is a research fellow working at the same institute.
Author: Yanqing Gao Publisher: World Scientific ISBN: 9814485845 Category : Technology & Engineering Languages : en Pages : 457
Book Description
Flexible robotic manipulators pose various challenges in research as compared to rigid robotic manipulators, ranging from system design, structural optimization, and construction to modeling, sensing, and control. Although significant progress has been made in many aspects over the last one-and-a-half decades, many issues are not resolved yet, and simple, effective, and reliable controls of flexible manipulators still remain an open quest. Clearly, further efforts and results in this area will contribute significantly to robotics (particularly automation) as well as its application and education in general control engineering. To accelerate this process, the leading experts in this important area present in this book the state of the art in advanced studies of the design, modeling, control and applications of flexible manipulators.
Author: Dan Zhang Publisher: CRC Press, Taylor & Francis Group, CRC Press is ISBN: 9781498764872 Category : Adaptive control systems Languages : en Pages : 0
Book Description
Cover -- Half title -- Title Page -- Copyright page -- Table of Contents -- Preface -- 1: From MRAC to Learning-Based MPC: The Emerging Importance of Machine Learning for Control of Robot Manipulators -- 2: Discussion on Model Reference Adaptive Control of Robotic Manipulators -- 3: Data-Based Learning for Uncertain Robotic Systems -- 4: Reinforcement Learning of Robotic Manipulators -- 5: Adaptive Control for Multi-Fingered Robot Hands -- 6: Output Feedback Adaptive Control of Uncertain Dynamical Systems with Event-Triggering -- 7: Event Sampled Adaptive Control of Robot Manipulators and Mobile Robot Formations -- 8: Design, Integration and Analysis of a Hybrid Controller for Multi Degrees of Freedom Serial Mechanisms -- 9: Adaptive Control of Modular Ankle Exoskeletons in Neurologically Disabled Populations -- 10: Open Architecture High Value Added Robot Manufacturing Cells -- 11: The Adaptive Control Algorithm for Manipulators with Joint Flexibility -- 12: Unification of Bipedal Robotic Walking using Quadratic Program-based Control Lyapunov Function: Applications to Regulation of ZMP and Angular Momentum -- 13: Robust Adaptive Nonlinear Control for Robotic Manipulators with Flexible Joints -- 14: Adaptive Switching Iterative Learning Control of Robot Manipulator -- 15: Adaptive Robust Control Design for Robot Manipulators Based on Online Estimation of the Lumped Time-Varying Model Uncertainties -- 16: Evaluation of Microgenetic and Microimmune Algorithms for Solving Inverse Kinematics of Hyper-redundant Robotic Manipulators On-line -- Index
Author: Andrew Dominic Marchese Publisher: ISBN: Category : Languages : en Pages : 236
Book Description
The goal of this thesis is to explore how autonomous robotic systems can be created with soft elastomer bodies powered by fluids. In this thesis we innovate in the design, fabrication, control, and experimental validation of both single and multi-segment soft fluidic elastomer robots. First, this thesis describes an autonomous fluidic elastomer robot that is both self-contained and capable of rapid, continuum body motion. Specifically, the design, modeling, fabrication, and control of a soft fish is detailed, focusing on enabling the robot to perform rapid escape responses. The robot employs a compliant body with embedded actuators emulating the slender anatomical form of a fish. In addition, the robot has a novel fluidic actuation system that drives body motion and has all the subsystems of a traditional robot on-board: power, actuation, processing, and control. At the core of the fish's soft body is an array of Fluidic Elastomer Actuators (FEAs). The fish is designed to emulate escape responses in addition to forward swimming because such maneuvers require rapid body accelerations and continuum body motion. These maneuvers showcase the performance capabilities of this self-contained robot. The kinematics and controllability of the robot during simulated escape response maneuvers are analyzed and compared to studies on biological fish. During escape responses, the soft-bodied robot is shown to have similar input-output relationships to those observed in biological fish. The major implication of this portion of the thesis is that a soft fluidic elastomer robot is shown to be both self-contained and capable of rapid body motion. Next, this thesis provides an approach to planar manipulation using soft fluidic elastomer robots. That is, novel approaches to design, fabrication, kinematic modeling, power, control, and planning as well as extensive experimental evaluations with multiple manipulator prototypes are presented. More specifically, three viable manipulator morphologies composed entirely from soft silicone rubber are explored, and these morphologies are differentiated by their actuator structures, namely: ribbed, cylindrical, and pleated. Additionally, three distinct casting-based fabrication processes are explored: lamination-based casting, retractable-pin-based casting, and lost-wax- based casting. Furthermore, two ways of fabricating a multiple DOF manipulator are explored: casting the complete manipulator as a whole, and casting single DOF segments with subsequent concatenation. An approach to closed-loop configuration control is presented using a piecewise constant curvature kinematic model, real-time localization data, and novel fluidic drive cylinders which power actuation. Multi-segment forward and inverse kinematic algorithms are developed and combined with the configuration controller to provide reliable task-space position control. Building on these developments, a suite of task-space planners are presented to demonstrate new autonomous capabilities from these soft robots such as: (i) tracking a path in free-space, (ii) maneuvering in confined environments, and (iii) grasping and placing objects. Extensive evaluations of these capabilities with physical prototypes demonstrate that manipulation with soft fluidic elastomer robots is viable. Lastly, this thesis presents a robotic manipulation system capable of autonomously positioning a multi-segment soft fluidic elastomer robot in three dimensions while subject to the self-loading effects of gravity. Specifically, an extremely soft robotic manipulator morphology that is composed entirely from low durometer elastomer, powered by pressurized air, and designed to be both modular and durable is presented. To understand the deformation of a single arm segment, a static physics-based model is developed and experimentally validated. Then, to kinematically model the multi-segment manipulator, a piece-wise constant curvature assumption consistent with more traditional continuum manipulators is used. Additionally, a complete fabrication process for this new manipulator is defined and used to make multiple functional prototypes. In order to power the robot's spatial actuation, a high capacity fluidic drive cylinder array is implemented, providing continuously variable, closed-circuit gas delivery. Next, using real-time localization data, a processing and control algorithm is developed that generates realizable kinematic curvature trajectories and controls the manipulator's configuration along these trajectories. A dynamic model for this multi-body fluidic elastomer manipulator is also developed along with a strategy for independently identifying all unknown components of the system: the soft manipulator, its distributed fluidic elastomer actuators, as well as its drive cylinders. Next, using this model and trajectory optimization techniques locally-optimal, open-loop control policies are found. Lastly, new capabilities offered by this soft fluidic elastomer manipulation system are validated with extensive physical experiments. These are: (i) entering and advancing through confined three-dimensional environments, (ii) conforming to goal shape-configurations within a sagittal plane under closed-loop control, and (iii) performing dynamic maneuvers we call grabs.
Author: Frank L. Lewis Publisher: CRC Press ISBN: 9780203026953 Category : Technology & Engineering Languages : en Pages : 646
Book Description
Robot Manipulator Control offers a complete survey of control systems for serial-link robot arms and acknowledges how robotic device performance hinges upon a well-developed control system. Containing over 750 essential equations, this thoroughly up-to-date Second Edition, the book explicates theoretical and mathematical requisites for controls design and summarizes current techniques in computer simulation and implementation of controllers. It also addresses procedures and issues in computed-torque, robust, adaptive, neural network, and force control. New chapters relay practical information on commercial robot manipulators and devices and cutting-edge methods in neural network control.
Author: Richard M. Murray Publisher: CRC Press ISBN: 1351469797 Category : Technology & Engineering Languages : en Pages : 503
Book Description
A Mathematical Introduction to Robotic Manipulation presents a mathematical formulation of the kinematics, dynamics, and control of robot manipulators. It uses an elegant set of mathematical tools that emphasizes the geometry of robot motion and allows a large class of robotic manipulation problems to be analyzed within a unified framework. The foundation of the book is a derivation of robot kinematics using the product of the exponentials formula. The authors explore the kinematics of open-chain manipulators and multifingered robot hands, present an analysis of the dynamics and control of robot systems, discuss the specification and control of internal forces and internal motions, and address the implications of the nonholonomic nature of rolling contact are addressed, as well. The wealth of information, numerous examples, and exercises make A Mathematical Introduction to Robotic Manipulation valuable as both a reference for robotics researchers and a text for students in advanced robotics courses.
Author: Hak Yi
Author: Hak Yi
Author: Yunong Zhang
Author: Geoffrey William Vernon
Author: Yanqing Gao
Author: 許銘全
Author: Dan Zhang
Author: Andrew Dominic Marchese
Author: Sabri Cetinkunt
Author: Frank L. Lewis
Author: Richard M. Murray