A Fault-Tolerant Method for Motion Planning of Industrial Redundant Manipulator

Nowadays industrial redundant manipulators have been playing important roles in manufacturing fields such as welding and assembling by performing repetitive and dull work. Such long-term industrial operations usually require redundant manipulators to keep good working conditions and maintain steadiness of joint actuation. However, some joints of redundant manipulators may fall into fault status after enduring long-period heavy manipulations, causing that the desired industrial tasks can not be accomplished accurately. In this paper, we propose a novel fault-tolerant method with simultaneous fault-diagnose function for motion planning and control of industrial redundant manipulators. The proposed approach is able to adaptively localize which joints run away from the normal state to be fault, and it can guarantee to finish the desired path tracking control even when these fault joints lose their velocity to actuate. Simulation and experiment results on a Kuka LBR iiwa manipulator demonstrate the efficiency of the proposed fault-tolerant method for motion control of the redundant manipulator

Modeling and Control of Flexible Link Manipulators

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

Parallel Manipulators

In recent years, parallel kinematics mechanisms have attracted a lot of attention from the academic and industrial communities due to potential applications not only as robot manipulators but also as machine tools. Generally, the criteria used to compare the performance of traditional serial robots and parallel robots are the workspace, the ratio between the payload and the robot mass, accuracy, and dynamic behaviour. In addition to the reduced coupling effect between joints, parallel robots bring the benefits of much higher payload-robot mass ratios, superior accuracy and greater stiffness; qualities which lead to better dynamic performance. The main drawback with parallel robots is the relatively small workspace. A great deal of research on parallel robots has been carried out worldwide, and a large number of parallel mechanism systems have been built for various applications, such as remote handling, machine tools, medical robots, simulators, micro-robots, and humanoid robots. This book opens a window to exceptional research and development work on parallel mechanisms contributed by authors from around the world. Through this window the reader can get a good view of current parallel robot research and applications

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

Es ist vorhersehbar, dass die Luftmanipulatoren in den nächsten Jahrzehnten für viele Aufgaben eingesetzt werden, die entweder zu gefährlich oder zu teuer sind, um sie mit herkömmlichen Methoden zu bewältigen. In dieser Arbeit wird eine neuartige Lösung für die Gesamtsteuerung von hochredundanten Luftmanipulationssystemen vorgestellt. Die Ergebnisse werden auf eine Referenzkonfiguration angewendet, die als universelle Plattform für die Durchführung verschiedener Luftmanipulationsaufgaben etabliert wird. Diese Plattform besteht aus einer omnidirektionalen Drohne und einem seriellen Manipulator. Um den modularen Regelungsentwurf zu gewährleisten, werden zwei rechnerisch effiziente Algorithmen untersucht, um den virtuellen Eingang den Aktuatorbefehlen zuzuordnen. Durch die Integration eines auf einem künstlichen neuronalen Netz basierenden Diagnosemoduls und der rekonfigurierbaren Steuerungszuordnung in den Regelkreis, wird die Fehlertoleranz für die Drohne erzielt. Außerdem wird die Motorsättigung durch Rekonfiguration der Geschwindigkeits- und Beschleunigungsprofile behandelt. Für die Beobachtung der externen Kräfte 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 sekundäre Aufgaben ausführt. Die Wirksamkeit der vorgestellten Lösungen wird durch umfangreiche Tests überprüft, 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

Prediction of Inverse Kinematics Solution of a Redundant manipulator using ANFIS

In this thesis, a method for forward and inverse kinematics analysis of a 5-DOF and a 7-DOF Redundant manipulator is proposed. Obtaining the trajectory and computing the required joint angles for a higher DOF robot manipulator is one of the important concerns in robot kinematics and control. When a robotic system possesses more degree of freedom (DOF) than those required to execute a given task is called Redundant Manipulator. The difficulties in solving the inverse kinematics (IK) equations of these redundant robot manipulator arises due to the presence of uncertain, time varying and non-linear nature of equations having transcendental functions. In this thesis, the ability of ANFIS (Adaptive Neuro-Fuzzy Inference System) is used to the generated data for solving inverse kinematics problem. The proposed hybrid neuro-fuzzy system combines the learning capabilities of neural networks with fuzzy inference system for nonlinear function approximation. A single-output Sugeno-type FIS (Fuzzy Inference System) using grid partitioning has been modeled in this work. The Denavit-Hartenberg (D-H) representation is used to model robot links and solve the transformation matrices of each joint. The forward kinematics and inverse kinematics for a 5-DOF and 7-DOF manipulator are analyzed systemically. ANFIS have been successfully used for prediction of IKs of 5-DOF and 7-DOF Redundant manipulator in this work. After comparing the output, it is concluded that the predicting ability of ANFIS is excellent as this approach provides a general frame work for combination of NN and fuzzy logic. The Efficiency of ANFIS can be concluded by observing the surface plot, residual plot and normal probability plot. This current study in using different nonlinear models for the prediction of the IKs of a 5-DOF and 7-DOF Redundant manipulator will give a valuable source of information for other modellers

Trends in vehicle motion control for automated driving on public roads

In this paper, we describe how vehicle systems and the vehicle motion control are affected by automated driving on public roads. We describe the redundancy needed for a road vehicle to meet certain safety goals. The concept of system safety as well as system solutions to fault tolerant actuation of steering and braking and the associated fault tolerant power supply is described. Notably restriction of the operational domain in case of reduced capability of the driving automation system is discussed. Further we consider path tracking, state estimation of vehicle motion control required for automated driving as well as an example of a minimum risk manoeuver and redundant steering by means of differential braking. The steering by differential braking could offer heterogeneous or dissimilar redundancy that complements the redundancy of described fault tolerant steering systems for driving automation equipped vehicles. Finally, the important topic of verification of driving automation systems is addressed

ROBOTIC INTERACTION AND COOPERATION. Industrial and rehabilitative applications

The main goal of the thesis is the development of human-robotic interaction control strategies, which enable close collaboration between human and robot. In this framework we studied two di erent aspects, with applications respectively in industrial and rehabilitation domains. In the rst part safety issues are examined on a scenario in which a robot manipulator and a human perform the same task and in the same workspace. During the task execution the human should be able to get into contact with the robot and in this case an estimation algorithm of both interaction forces and contact point is proposed in order to guarantee safety conditions. At the same time, all the unintended contacts have to be avoided, and a suitable post collision strategy has been studied to move away the robot from the collision area or to reduce the impact e orts. However, the second part of the thesis focus on the cooperation between an orthesis and a patient. Indeed, in order to support a rehabilitation process, gait parameters, such as hip and knee angles or the beginning of a gait phase, have been estimated. For this purpose a sensor system, consisting of accelerometers and gyroscopes, and algorithms, developed in order to avoid the error accumulation due to the gyroscopes drift and the vibrations related to the beginning of the stance phase due to the accelerometers, have been proposed.The main goal of the thesis is the development of human-robotic interaction control strategies, which enable close collaboration between human and robot. In this framework we studied two di erent aspects, with applications respectively in industrial and rehabilitation domains. In the rst part safety issues are examined on a scenario in which a robot manipulator and a human perform the same task and in the same workspace. During the task execution the human should be able to get into contact with the robot and in this case an estimation algorithm of both interaction forces and contact point is proposed in order to guarantee safety conditions. At the same time, all the unintended contacts have to be avoided, and a suitable post collision strategy has been studied to move away the robot from the collision area or to reduce the impact e orts. However, the second part of the thesis focus on the cooperation between an orthesis and a patient. Indeed, in order to support a rehabilitation process, gait parameters, such as hip and knee angles or the beginning of a gait phase, have been estimated. For this purpose a sensor system, consisting of accelerometers and gyroscopes, and algorithms, developed in order to avoid the error accumulation due to the gyroscopes drift and the vibrations related to the beginning of the stance phase due to the accelerometers, have been proposed

Advanced Strategies for Robot Manipulators

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

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 authors’ 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