A robotics toolbox for MATLAB

doi:10.1109/100.486658

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A robotics toolbox for MATLAB

Journal Article•DOI•

A robotics toolbox for MATLAB

Peter Corke¹•Institutions (1)

Commonwealth Scientific and Industrial Research Organisation¹

01 Mar 1996-IEEE Robotics & Automation Magazine (IEEE)-Vol. 3, Iss: 1, pp 24-32

TL;DR: The Robotics Toolbox is a software package that allows a MATLAB user to readily create and manipulate datatypes fundamental to robotics such as homogeneous transformations, quaternions and trajectories.

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Abstract: The Robotics Toolbox is a software package that allows a MATLAB user to readily create and manipulate datatypes fundamental to robotics such as homogeneous transformations, quaternions and trajectories. Functions provided, for arbitrary serial-link manipulators, include forward and inverse kinematics, Jacobians, and forward and inverse dynamics. This article introduces the Toolbox in tutorial form, with examples chosen to demonstrate a range of capabilities. The complete Toolbox and documentation is freely available via anonymous ftp.

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Journal Article•DOI•

Multirotor Aerial Vehicles: Modeling, Estimation, and Control of Quadrotor

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Robert Mahony¹, Vijay Kumar², Peter Corke³•Institutions (3)

Australian National University¹, University of Pennsylvania², Queensland University of Technology³

28 Aug 2012-IEEE Robotics & Automation Magazine

TL;DR: In this article, a tutorial for modeling, estimation, and control for multi-rotor aerial vehicles that includes the common four-rotors or quadrotors case is presented.

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Abstract: This article provides a tutorial introduction to modeling, estimation, and control for multirotor aerial vehicles that includes the common four-rotor or quadrotor case.

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1,241 citations

Journal Article•DOI•

Graspit! A versatile simulator for robotic grasping

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A.T. Miller¹, Peter K. Allen¹•Institutions (1)

Columbia University¹

27 Dec 2004-IEEE Robotics & Automation Magazine

TL;DR: The different types of world elements and the general robot definition are discussed and the robot library is presented, and the grip analysis and visualization method were presented.

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Abstract: A robotic grasping simulator, called Graspit!, is presented as versatile tool for the grasping community. The focus of the grasp analysis has been on force-closure grasps, which are useful for pick-and-place type tasks. This work discusses the different types of world elements and the general robot definition, and presented the robot library. The paper also describes the user interface of Graspit! and present the collision detection and contact determination system. The grasp analysis and visualization method were also presented that allow a user to evaluate a grasp and compute optimal grasping forces. A brief overview of the dynamic simulation system was provided.

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1,042 citations

Cites methods from "A robotics toolbox for MATLAB"

...We have modeled the geometry of the links using approximate dimensions, and we have used the mass parameters found in the Robotics Toolbox for MATLAB [6]....
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...Of course, there are already several commercial robotics simulators available, including Delmia’s IGRIP, Flow Software Technologies’ Workspace5, MCS.Software’s ADAMS, and the Easy-Rob system, as well as past and present research projects in robot simulation, including GRASP (an early robot arm simulator) [4], IRODESS [5], the Robotics Toolbox for MATLAB [6], RoboSiM [7], and Simpact [8], but none of these focus on the grasping problem....
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...Some of the features of this system include: ◆ a robot library that includes several hand models, a Puma arm, and a simplified mobile base ◆ a flexible robot definition that makes it possible to import new robot designs BY ANDREW T. MILLER AND PETER K. ALLEN © 20 01 IM A G E S TA T E 1070-9932/04/$20.00©2004 IEEEIEEE Robotics & Automation Magazine DECEMBER 2004110 DECEMBER 2004 IEEE Robotics & Automation Magazine 111 ◆ the ability to connect robots to build a manipulation platform ◆ the ability to import obstacle models to build a complete working environment for the robots ◆ an intuitive interactive interface, as well as an external interface to MATLAB ◆ a fast collision detection and contact determination system ◆ grasp analysis routines that evaluate the quality of a grasp on the fly ◆ visualization methods that can show the weak point of a grasp and create projections of the grasp wrench space ◆ a dynamics engine that computes robot and object motions under the influence of external forces and contacts ◆ a simple trajectory generator and control algorithms that compute the joint forces necessary to follow the trajectory....
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...Software’s ADAMS, and the Easy-Rob system, as well as past and present research projects in robot simulation, including GRASP (an early robot arm simulator) [4], IRODESS [5], the Robotics Toolbox for MATLAB [6], RoboSiM [7], and Simpact [8], but none of these focus on the grasping problem....
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The mathematics of coordinated control of prosthetic arms and manipulators.

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D. E. Whitney¹•Institutions (1)

Massachusetts Institute of Technology¹

01 Nov 1972

569 citations

Dissertation•

Evaluation of gaussian processes and other methods for non-linear regression

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Geoffrey E. Hinton¹, Carl Edward Rasmussen¹•Institutions (1)

Max Planck Society¹

01 Jan 1997

TL;DR: It is shown that a Bayesian approach to learning in multi-layer perceptron neural networks achieves better performance than the commonly used early stopping procedure, even for reasonably short amounts of computation time.

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Abstract: This thesis develops two Bayesian learning methods relying on Gaussian processes and a rigorous statistical approach for evaluating such methods. In these experimental designs the sources of uncertainty in the estimated generalisation performances due to both variation in training and test sets are accounted for. The framework allows for estimation of generalisation performance as well as statistical tests of significance for pairwise comparisons. Two experimental designs are recommended and supported by the DELVE software environment. Two new non-parametric Bayesian learning methods relying on Gaussian process priors over functions are developed. These priors are controlled by hyperparameters which set the characteristic length scale for each input dimension. In the simplest method, these parameters are fit from the data using optimization. In the second, fully Bayesian method, a Markov chain Monte Carlo technique is used to integrate over the hyperparameters. One advantage of these Gaussian process methods is that the priors and hyperparameters of the trained models are easy to interpret. The Gaussian process methods are benchmarked against several other methods, on regression tasks using both real data and data generated from realistic simulations. The experiments show that small datasets are unsuitable for benchmarking purposes because the uncertainties in performance measurements are large. A second set of experiments provide strong evidence that the bagging procedure is advantageous for the Multivariate Adaptive Regression Splines (MARS) method. The simulated datasets have controlled characteristics which make them useful for understanding the relationship between properties of the dataset and the performance of different methods. The dependency of the performance on available computation time is also investigated. It is shown that a Bayesian approach to learning in multi-layer perceptron neural networks achieves better performance than the commonly used early stopping procedure, even for reasonably short amounts of computation time. The Gaussian process methods are shown to consistently outperform the more conventional methods.

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467 citations

Journal Article•DOI•

ViSP for visual servoing: a generic software platform with a wide class of robot control skills

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Eric Marchand¹, F. Spindler¹, François Chaumette¹•Institutions (1)

University of Rennes 1¹

01 Dec 2005-IEEE Robotics & Automation Magazine

TL;DR: A fully functional modular architecture that allows fast development of visual servoing applications, ViSP (Visual Servoing Platform), which takes the form of a library which can be divided in three main modules: control processes, canonical vision-based tasks that contain the most classical linkages, and real-time tracking.

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Abstract: ViSP (Visual Servoing Platform), a fully functional modular architecture that allows fast development of visual servoing applications, is described. The platform takes the form of a library which can be divided in three main modules: control processes, canonical vision-based tasks that contain the most classical linkages, and real-time tracking. ViSP software environment features independence with respect to the hardware, simplicity, extendibility, and portability. ViSP also features a large library of elementary tasks with various visual features that can be combined together, an image processing library that allows the tracking of visual cues at video rate, a simulator, an interface with various classical framegrabbers, a virtual 6-DOF robot that allows the simulation of visual servoing experiments, etc. The platform is implemented in C++ under Linux.

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463 citations

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References

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Open Access

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Book•

Robot Manipulators: Mathematics, Programming, and Control

[...]

Richard P. Paul

02 Nov 1981

2,361 citations

Book•

Introduction to Robotics

[...]

Philip Mckerrow

01 May 1991

TL;DR: Invention to Robotics provides both an introductory text for students coming new to the field and a survey of the state of the art for professional practitioners.

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Abstract: From the Publisher: Introduction to Robotics provides both an introductory text for students coming new to the field and a survey of the state of the art for professional practitioners.

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2,354 citations

Journal Article•DOI•

Efficient Dynamic Computer Simulation of Robotic Mechanisms

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M. W. Walker¹, David E. Orin²•Institutions (2)

Nordson Corporation¹, Ohio State University²

01 Sep 1982-Journal of Dynamic Systems Measurement and Control-transactions of The Asme

791 citations

The mathematics of coordinated control of prosthetic arms and manipulators.

[...]

D. E. Whitney¹•Institutions (1)