This article provides a tutorial introduction to visual servo control of robotic manipulators. Since the topic spans many disciplines our goal is limited to providing a basic conceptual framework. We begin by reviewing the prerequisite topics from robotics and computer vision, including a brief review of coordinate transformations, velocity representation, and a description of the geometric aspects of the image formation process. We then present a taxonomy of visual servo control systems. The two major classes of systems, position-based and image-based systems, are then discussed in detail. Since any visual servo system must be capable of tracking image features in a sequence of images, we also include an overview of feature-based and correlation-based methods for tracking. We conclude the tutorial with a number of observations on the current directions of the research field of visual servo control.

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A tutorial on visual servo control

A tutorial account of variable structure control with sliding mode is presented. The purpose is to introduce in a concise manner the fundamental theory, main results, and practical applications of this powerful control system design approach. This approach is particularly attractive for the control of nonlinear systems. Prominent characteristics such as invariance, robustness, order reduction, and control chattering are discussed in detail. Methods for coping with chattering are presented. Both linear and nonlinear systems are considered. Future research areas are suggested and an extensive list of references is included. >

Variable structure control: a survey

Mobile robots range from the Mars Pathfinder mission's teleoperated Sojourner to the cleaning robots in the Paris Metro. This text offers students and other interested readers an introduction to the fundamentals of mobile robotics, spanning the mechanical, motor, sensory, perceptual, and cognitive layers the field comprises. The text focuses on mobility itself, offering an overview of the mechanisms that allow a mobile robot to move through a real world environment to perform its tasks, including locomotion, sensing, localization, and motion planning. It synthesizes material from such fields as kinematics, control theory, signal analysis, computer vision, information theory, artificial intelligence, and probability theory. The book presents the techniques and technology that enable mobility in a series of interacting modules. Each chapter treats a different aspect of mobility, as the book moves from low-level to high-level details. It covers all aspects of mobile robotics, including software and hardware design considerations, related technologies, and algorithmic techniques.] This second edition has been revised and updated throughout, with 130 pages of new material on such topics as locomotion, perception, localization, and planning and navigation. Problem sets have been added at the end of each chapter. Bringing together all aspects of mobile robotics into one volume, Introduction to Autonomous Mobile Robots can serve as a textbook or a working tool for beginning practitioners.

http://www.gbv.de/dms/hebis-darmstadt/toc/120387220.pdf

Introduction to Autonomous Mobile Robots

The technology of hydrodynamic modeling and marine craft motion control systems has progressed greatly in recent years. This timely survey includes the latest tools for analysis and design of advanced guidance, navigation and control systems and presents new material on underwater vehicles and surface vessels. Each section presents numerous case studies and applications, providing a practical understanding of how model-based motion control systems are designed.

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Handbook of Marine Craft Hydrodynamics and Motion Control: Fossen/Handbook of Marine Craft Hydrodynamics and Motion Control

Nonlinear dynamical systems have been used in many disciplines to model complex behaviors, including biological motor control, robotics, perception, economics, traffic prediction, and neuroscience. While often the unexpected emergent behavior of nonlinear systems is the focus of investigations, it is of equal importance to create goal-directed behavior e.g., stable locomotion from a system of coupled oscillators under perceptual guidance. Modeling goal-directed behavior with nonlinear systems is, however, rather difficult due to the parameter sensitivity of these systems, their complex phase transitions in response to subtle parameter changes, and the difficulty of analyzing and predicting their long-term behavior; intuition and time-consuming parameter tuning play a major role. This letter presents and reviews dynamical movement primitives, a line of research for modeling attractor behaviors of autonomous nonlinear dynamical systems with the help of statistical learning techniques. The essence of our approach is to start with a simple dynamical system, such as a set of linear differential equations, and transform those into a weakly nonlinear system with prescribed attractor dynamics by means of a learnable autonomous forcing term. Both point attractors and limit cycle attractors of almost arbitrary complexity can be generated. We explain the design principle of our approach and evaluate its properties in several example applications in motor control and robotics.

/pdf/dynamical-movement-primitives-learning-attractor-models-for-gv4xupyvzg.pdf

Dynamical movement primitives: Learning attractor models for motor behaviors

A novel approach to the analysis of modulation processes in power convertors is developed. The single harmonic components of the modulator output spectrum are given in terms of series with fast convergence rate. The method set forth is based on the theory of the Kapteyn series. Both the cases of rational and irrational frequency ratio are treated and some typical peculiarities of the modulation processes are stressed.

http://ieeexplore.ieee.org/iel5/5247218/5252726/05252742.pdf

Analysis of modulation processes in power convertors

The increased demand on robotic manipulator performance leads to the use of advanced control structures. The general task of a robot control system is to enable the manipulator end-effector to follow prescribed motion trajectories, planned in a suitable coordinate frame related to the manipulator task space, and to exert prescribed forces when the end-effector impacts the environment. During latest years several control schemes have been proposed in the literature, such as pure force control, compliance control, impedance control, and hybrid control. Hybrid control is the only control strategy which allows for simultaneous control of motion and force; the structure of this control system is modified by means of opportune selection matrices which are defined according to the task requirement. This paper presents a new force control method which may be thought as logically derived from compliance control and impedance control for which only a reference position is usually assigned. The attractive feature of the proposed control is that it also allows for a reference force to be assigned. In this way one may obtain analogous performance to hybrid control without adopting selection matrices. The advantage gained with this choice lies in the achievement of a degree of robustness of the control scheme to inaccurate environment modeling.

Force/position control of manipulators in task space with dominance in force

On dynamic modelling of gear-driven rigid robot manipulators

Adaptive model following control systems for a class of nonlinear multivariable plants

A novel algorithmic approach to the reachable workspace determination is presented. The reachable workspace is that volume of space which the end effector can reach. The present work is restricted to special geometries which have a 2R or a 3R planar pair, but the resulting algorithm appears to be applicable to any manipulator geometry. Computation results are presented for a 2R and a 3R redundant planar pair. >

Lorenzo Sciavicco

Papers

Analysis of modulation processes in power convertors

Force/position control of manipulators in task space with dominance in force

On dynamic modelling of gear-driven rigid robot manipulators

Adaptive model following control systems for a class of nonlinear multivariable plants

An algorithm to compute the reachable workspace for 2R and 3R planar pair mechanical arms