Computer Animation Rick Parent Computer Animation Algorithms and Techniques Kinematic Linkages.

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Presentation transcript:

Computer Animation Rick Parent Computer Animation Algorithms and Techniques Kinematic Linkages

Computer Animation Rick Parent Hierarchical Modeling Relative motion Constrains motion Reduces dimensionality Parent-child relationship Simplifies motion specification

Computer Animation Rick Parent Modeling & animating hierarchies 3 aspects 1. Linkages & Joints – the relationships 2. Data structure – how to represent such a hierarchy 3. Converting local coordinate frames into global space

Computer Animation Rick Parent Some terms Joint – allowed relative motion & parameters Joint Limits – limit on valid joint angle values Link – object involved in relative motion Linkage – entire joint-link hierarchy Armature – same as linkage End effector – most distant link in linkage Articulation variable – parameter of motion associated with joint Pose – configuration of linkage using given set of joint angles Pose vector – complete set of joint angles for linkage Arc – of a tree data structure – corresponds to a joint Node – of a tree data structure – corresponds to a link

Computer Animation Rick Parent Use of hierarchies in animation Forward Kinematics (FK) animator specifies values of articulation variables Inverse Kinematics (IK) animator specifies final desired global transform for end effector (and possibly other linkages) global transform for each linkage is computed Values of articulation variables are computed

Computer Animation Rick Parent Forward & Inverse Kinematics

Computer Animation Rick Parent Joints – relative movement

Computer Animation Rick Parent Complex Joints

Computer Animation Rick Parent Hierarchical structure

Computer Animation Rick Parent Tree structure

Computer Animation Rick Parent Tree structure

Computer Animation Rick Parent Tree structure

Computer Animation Rick Parent Relative movement

Computer Animation Rick Parent Relative movement

Computer Animation Rick Parent Tree structure

Computer Animation Rick Parent Tree structure

Computer Animation Rick Parent Implementation note Nodes & arcs NODE Pointer to data Data transformation Pointer to arcs ARC Transform of one next node relative to parent node Articulation transform Pointer to node

Computer Animation Rick Parent Implementation note Representing arbitrary number of children with fixed-length data structure Node points to first child Each child points to sibling Last sibling points to NULL In node: arcPtr for 1 st child In arc: arcPtr for sibling Use array of pointers to children In node, arcPtr[]

Computer Animation Rick Parent Tree traversal traverse (arcPtr,matrix) { // concatenate arc matrices matrix = matrix*arcPtr->Lmatrix matrix = matrix*arcPtr->Amatrix; // get node and transform data nodePtr=acrPtr->nodePtr push (matrix) matrix = matrix * nodePTr->matrix aData = transformData(matrix,dataPTr) draw(aData) matrix = pop(); // process children If (nodePtr->arcPtr != NULL) { nextArcPtr = nodePTr-> arcPtr while (nextArcPtr != NULL) { push(matrix) traverse(nextArcPtr,matrix) matrix = pop() nextArcPtr = nextArcPtr->arcPtr } L A d,M

Computer Animation Rick Parent OpenGL Single linkage glPushMatrix(); For (i=0; i<NUMDOFS; i++) { glRotatef(a[i],axis[i][0], axis[i][1], axis[i][2]); if (linkLen[i] != 0.0) { draw_linkage(linkLen[i]); glTranslatef(0.0,linkLen[i],0.0); } glPopMatrix(); A[i] – joint angle Axis[i] – joint axis linkLen[i] – length of link OpenGL concatenates matrices

Computer Animation Rick Parent Inverse kinematics Given goal position (and orientation) for end effector Compute internal joint angles If simple enough => analytic solution Else => numeric iterative solution

Computer Animation Rick Parent Inverse kinematics - spaces Configuration space Reachable workspace Dextrous workspace

Computer Animation Rick Parent Analytic inverse kinematics

Computer Animation Rick Parent IK - numeric If linkage is too complex to solve analytically Desired change from this specific pose Compute set of changes to the pose to effect that change Solve iteratively – numerically solve for step toward goal E.g., human arm is typically modeled as or linkage

Computer Animation Rick Parent IK math notation

Computer Animation Rick Parent IK – chain rule

Computer Animation Rick Parent Inverse Kinematics - Jacobian Desired motion of end effector Unknown change in articulation variables The Jacobian is the matrix relating the two: it’s a function of current variable values

Computer Animation Rick Parent Inverse Kinematics - Jacobian Change in position Change in orientation Jacobian Change in articulation variables

Computer Animation Rick Parent IK – computing the Jacobian Only valid instantaneously (need to convert to global coordinates) Change in position Change in orientation

Computer Animation Rick Parent IK - configuration

Computer Animation Rick Parent IK – compute positional change vectors induced by changes in joint angles Instantaneous positional change vectors Desired change vector One approach to IK computes linear combination of change vectors that equal desired vector

Computer Animation Rick Parent IK – compute position and axis of joints Set identity matrix for (i=0; i<NUMDOFS; i++) { record_transformed_joint(i) glRotate(angle[i],axis[i][0],axis[i][1],axis[i][2]); append_rotation(angle[i],axis[i][0],axis[i][1],axis[i][2]); if (linkLen[i] != 0) { draw_linkage(linkLen[i]); glTranslatef(0.0,linkLen[i],0.0); append_translation(0,linkLen[i],0); } record_endEffector();

Computer Animation Rick Parent IK – append rotation If joint axis is: one of major axes: 3 cases ofsimple rotation Arbitrary axis – angle-axis to matrix conversion IK – append translation Form translation matrix Matrix Transformed coordinate system Position Transforms axis of rotation

Computer Animation Rick Parent IK – record joint information Joint position – last column of matrix Joint coordinate system – upper left 3x3 submatrix Joint axis – transform local joint axis vector by matrix

Computer Animation Rick Parent IK - singularity Some singular configurations are not so easily recognizable Near singular configurations are also problematic – why?

Computer Animation Rick Parent Inverse Kinematics - Numeric Given Current configuration Goal position/orientation Determine Goal vector Positions & local coordinate systems of interior joints (in global coordinates) Jacobian Solve & take small step – or clamp acceleration or clamp velocity Repeat until: Within epsilon of goal Stuck in some configuration Taking too long Is in same form as more recognizable :

Computer Animation Rick Parent Solving If J not square, usually under-constrained: more DoFs than constraints Requires use of pseudo-inverse of Jacobian If J square, compute inverse, J -1

Computer Animation Rick Parent Solving Avoid direct computation of inverse by substitution solving Ax=B form, then substituting back

Computer Animation Rick Parent IK – Jacobian solution

Computer Animation Rick Parent IK – Jacobian solution - problem When goal is out of reach Bizarre undulations can occur As armature tries to reach the unreachable Add a damping factor

Computer Animation Rick Parent IK – Jacobian w/ damped least squares Undamped form: Damped form with user parameter:

Computer Animation Rick Parent IK – Jacobian w/ control term Take advantage of redundant manipulators - Allow user to set parameter that urges DOF to a certain value Does not enforce joint limit constraints, but can be used to keep joint angles at mid-range values Physical systems (i.e. robotics) and synthetic character simulation (e.g., human figure) have limits on joint values IK allows joint angle to have any value Difficult (computationally expensive) to incorporate hard constraints on joint values

Computer Animation Rick Parent IK – Jacobian w/ control term Change to the pose parameter in the form of the control term adds nothing to the velocity

Computer Animation Rick Parent IK – Jacobian w/ control term All bias to 0 Top gains = {0.1, 0.5, 0.1} Bottom gains = {0.1, 0.1, 0.5}

Computer Animation Rick Parent IK – alternate Jacobian Jacobian formulated to pull the goal toward the end effector Use same method to form Jacobian but use goal coordinates instead of end-effector coordinates

Computer Animation Rick Parent IK – Transpose of the Jacobian Compute how much the change vector contributes to the desired change vector: Project joint change vector onto desired change vector Dot product of joint change vector and desired change vector => Transpose of the Jacobian

Computer Animation Rick Parent IK – Transpose of the Jacobian

Computer Animation Rick Parent IK – cyclic coordinate descent Consider one joint at a time, from outside in At each joint, choose update that best gets end effector to goal position In 2D – pretty simple Heuristic solution EndEffector Goal JiJi axis i

Computer Animation Rick Parent IK – cyclic coordinate descent In 3D, a bit more computation is needed

Computer Animation Rick Parent IK – 3D cyclic coordinate descent First – goal has to be projected onto plane defined by axis (normal to plane) and EF EndEffector Goal JiJi axis i Projected goal Second– determine angle at joint

Computer Animation Rick Parent IK – cyclic coordinate descent – 3D Other orderings of processing joints are possible Because of its procedural nature Lends itself to enforcing joint limits Easy to clamp angular velocity

Computer Animation Rick Parent Inverse kinematics - review Analytic method Forming the Jacobian Numeric solutions Pseudo-inverse of the Jacobian J + with damping J + with control term Alternative Jacobian Transpose of the Jacobian Cyclic Coordinate Descent (CCD)

Computer Animation Rick Parent Inverse kinematics - orientation Change in orientation at end-effector is same as change at joint JiJi axis i EF

Computer Animation Rick Parent Inverse kinematics - orientation How to represent orientation (at goal, at end-effector)? How to compute difference between orientations? How to represent desired change in orientation in V vector? How to incorporate into IK solution? Matrix representation: M g, M ef Difference M d = M ef -1 M g Use scaled axis of rotation:  (a x a y a z ): Extract quaternion from M d Extract (scaled) axis from quaternion E.g., use Jacobian Transpose method: Use projection of scaled joint axis onto extracted axis