1 / 4

Programming Assignment #3

Programming Assignment #3. Inverse Kinematics for Human Body Requirements Compute Jacobian matrix and its pseudo-inverse Make the flexibility of each joint adjustable Specify both goal position and orientation of a limb Implement Euler integration You may leave the skeletal root fixed.

Télécharger la présentation

Programming Assignment #3

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Programming Assignment #3 • Inverse Kinematics for Human Body • Requirements • Compute Jacobian matrix and its pseudo-inverse • Make the flexibility of each joint adjustable • Specify both goal position and orientation of a limb • Implement Euler integration • You may leave the skeletal root fixed

  2. Programming Assignment #3 • Optional Requirements • Allow multiple constraints to be specified • Make the skeletal root floating • Formulate objective function and implement line minimization • Implement a user-interface to drag an arbitrary body part

  3. Sample Code Nonlinear Programming gradient_descent( d, num_dof, tolerance, iter, f, energyFunc, leastSquareDirection); Objective function to minimize static float energyFunc( vectorNconst&d ); Least Square of Jacobian Matrix static float leastSquareDirection( vectorNconst&d, vectorN& dp )

  4. Sample Code static float gradientFuncLS( vectorN const&d, vectorN& dp ) { tPosture = oPosture; tPosture.addDisplacement( d ); J = computeJacobian(); static matrixN Jt; Jt.transpose( J ); static matrixN Jp; Jp.mult( Jt, J ); static vectorN bp; bp.mult( Jt, b ); dp.solve( Jp, bp ); }

More Related