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Robotics: Modelling, Planning and Control

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TLDR
Robotics provides the basic know-how on the foundations of robotics: modelling, planning and control, suitable for use in senior undergraduate and graduate courses in automation and computer, electrical, electronic and mechanical engineering courses with strong robotics content.
Abstract
The classic text on robot manipulators now covers visual control, motion planning and mobile robots too! Robotics provides the basic know-how on the foundations of robotics: modelling, planning and control. The text develops around a core of consistent and rigorous formalism with fundamental and technological material giving rise naturally and with gradually increasing difficulty to more advanced considerations. The theory of manipulator structures presented in the early part of the book encompasses: the fundamentals: kinematics, statics and trajectory planning; and the technology of actuators, sensors and control units. Subsequently, more advanced instruction is given in: dynamics and motion control of robot manipulators; mobile robots; motion planning; and interaction with the environment using exteroceptive sensory data (force and vision). Appendices ensure that students will have access to a consistent level of background in basic areas such as rigid-body mechanics, feedback control, and others. Problems are raised and the proper tools established to find engineering-oriented solutions rather than to focus on abstruse theoretical methodology. To impart practical skill, more than 60 examples and case studies are carefully worked out and interwoven through the text, with frequent resort to simulation. In addition, nearly 150 end-of-chapter problems are proposed, and the book is accompanied by a solutions manual (downloadable from www.springer.com/978-1-84628-641-4) containing the MATLAB code for computer problems; this is available free of charge to those adopting Robotics as a textbook for courses. This text is suitable for use in senior undergraduate and graduate courses in automation and computer, electrical, electronic and mechanical engineering courses with strong robotics content.

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Journal ArticleDOI

A Learning Framework to inverse kinematics of high DOF redundant manipulators

TL;DR: In this paper, some redundant manipulator’s joints are parameterized through workspace clustering and configuration space clustering of the redundant manipulators, using the growing neural gas network (GNG) and a neighborhood function (NF) in configurationspace clustering.
Proceedings ArticleDOI

Visual Odometry for autonomous robot navigation through efficient outlier rejection

TL;DR: An accurate computationally-efficient VO algorithm relying exclusively on stereo vision is proposed, coupled with a non-iterative outlier detection technique capable of efficiently discarding outliers of matched features.
Journal ArticleDOI

Point-to-Point Collision-Free Trajectory Planning for Mobile Manipulators

TL;DR: The collision-free trajectory planning method subject to control constraints for mobile manipulators is presented and guarantees satisfying control limitations resulting from capabilities of robot actuators by applying the trajectory scaling approach.
Journal ArticleDOI

Isotropic Compliance in E(3): Feasibility and Workspace Mapping

TL;DR: In this article, the authors introduce the concept of control gain ratio for each specific single-input/single-output joint control law in order to limit the maximum gain required to achieve the isotropic compliance condition.
Journal ArticleDOI

Application of Miniaturized Sensors to Unmanned Aerial Systems, A New Pathway for the Survey of Polluted Areas: Preliminary Results

TL;DR: The proposal for a new system architecture derived from the integration of a low-cost laser-based network of detectors for pollutants interfaced with a more sophisticated layout mounted on an unmanned aerial vehicle (UAV) able to identify the nature and the amount of a release is considered.