By Etienne Dombre, Wisama Khalil

ISBN-10: 184704560X

ISBN-13: 9781847045607

ISBN-10: 190520910X

ISBN-13: 9781905209101

This publication provides the latest learn effects on modeling and keep watch over of robotic manipulators.

  • Chapter 1 provides unified instruments to derive direct and inverse geometric, kinematic and dynamic versions of serial robots and addresses the difficulty of id of the geometric and dynamic parameters of those versions.
  • Chapter 2 describes the most beneficial properties of serial robots, the several architectures and the equipment used to procure direct and inverse geometric, kinematic and dynamic types, paying specified cognizance to singularity research.
  • Chapter three introduces international and native instruments for functionality research of serial robots.
  • Chapter four provides an unique optimization method for point-to-point trajectory iteration accounting for robotic dynamics.
  • Chapter five provides common keep watch over options within the joint house and activity house at no cost movement (PID, computed torque, adaptive dynamic keep an eye on and variable constitution keep an eye on) and restricted movement (compliant force-position control).
  • In Chapter 6 , the idea that of vision-based keep an eye on is built and Chapter 7 is dedicated to express factor of robots with versatile hyperlinks. effective recursive Newton-Euler algorithms for either inverse and direct modeling are offered, in addition to keep watch over tools making sure place environment and vibration damping.

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Extra resources for Robot Manipulators: Modeling, Performance Analysis and Control

Example text

When f is only a function of q and ξ, the method of calibration is called autonomous method since it does not need an external sensor. 58] ⎡f (q(1), x(1), ) ⎤ ⎥ F = ⎢⎢ ... 59] with: ρ being the residual vector or the error vector. 60] with: ⎡ ∆y (1) ⎤ ⎡ φ(1) ⎤ ∆Y = ⎢⎢ ... ⎥⎥ , W = ⎢⎢ ... ⎥⎥ ⎢⎣ ∆y (e) ⎥⎦ ⎢⎣ φ(e) ⎥⎦ The matrix W is the observation matrix. e number of equations is >>Npar, where p represents the number of equations of the calibration model. 2. Identifying the geometric parameters Before solving the calibration equations, it is necessary to verify that the vector of unknown elements contains only the identifiable parameters in order to obtain an observation matrix W of maximum rank.

We note that the majority of calibration methods provide acceptable condition number for arbitrary configurations [KHA 00]. 3. 60] and the update of geometric parameters after each iteration. The method using the differential model gives good results for rigid robots. 67] where W+ indicates the pseudo-inverse matrix of W. If W is of maximal rank, the explicit form of W+ is given by (WT W)-1 WT. We calculate an estimate of standard deviation for the values identified by using matrix W in terms of the estimated parameters.

The nominal values of these parameters are known and generally provided by the manufacturer. It is then a matter of identifying the distance between the nominal values and the real values [HOL 89], [KHA 02]. 2. 1; – 0Tn: transformation matrix of the robot. 42], we distinguish three types of parameters: the geometric parameters of the robot required to calculate the matrix 0Tn, the parameters defining matrix Z and those defining matrix E. 1. 3] is based on (αj, dj, θj, rj). In the case where two consecutive axes j-1 and j are parallel, the choice of xj-1 is not unique, which leads to an arbitrary choice of the position of xj-1.

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Robot Manipulators: Modeling, Performance Analysis and Control by Etienne Dombre, Wisama Khalil


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