Animation CS 551 / 651

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Animation CS 551 / 651. Kinematics Lecture 09. Sarcos Humanoid. Kinematics. The study of object movements irrespective of their speed or style of movement. Degrees of Freedom (DOFs). The variables that affect an object’s orientation How many degrees of freedom when flying?. - PowerPoint PPT Presentation

Transcript of Animation CS 551 / 651

  • AnimationCS 551 / 651

    KinematicsLecture 09Sarcos Humanoid

  • KinematicsThe study of object movements irrespective of their speed or style of movement

  • Degrees of Freedom(DOFs)The variables that affect an objects orientationHow many degrees of freedom when flying?Sixx, y, and z positionsroll, pitch, and yawSo the kinematics of this airplane permit movement anywhere in three dimensions

  • Degrees of FreedomHow about this robot arm?Six again2-base, 1-shoulder, 1-elbow, 2-wrist

  • The set of all possible positions (defined by kinematics) an object can attainConfiguration Space

  • Work Space vs. Configuration SpaceWork spaceThe space in which the object existsDimensionalityR3 for most things, R2 for planar armsConfiguration spaceThe space that defines the possible object configurationsDegrees of FreedomThe number of parameters that necessary and sufficient to define position in configuration

  • More examplesA point on a planeA point in spaceA point moving on a line in space

  • A matter of controlIf your animation adds energy at a particular DOF, that is a controlled DOFHigh DOF, no controlLow DOF, high control

  • Hierarchical Kinematic ModelingA family of parent-child spatial relationships are functionally definedMoon/Earth/Sun movementsArticulations of a humanoidLimb connectivity is built into model (joints) and animation is easier

  • Robot Parts/TermsLinksEnd effectorFrameRevolute JointPrismatic Joint

  • More Complex Joints3 DOF jointsGimbalSpherical (doesnt possess singularity)2 DOF jointsUniversal

  • Hierarchy RepresentationModel bodies (links) as nodes of a treeAll body frames are local (relative to parent) Transformations affecting root affect all childrenTransformations affecting any node affect all its childrenROOT

  • Forward vs. Inverse KinematicsForward KinematicsCompute configuration (pose) given individual DOF valuesGood for simulationInverse KinematicsCompute individual DOF values that result in specified end effector positionGood for control

  • Forward KinematicsTraverse kinematic tree and propagate transformations downwardUse stackCompose parent transformation with childsPop stack when leaf is reached

  • Denavit-Hartenberg (DH) NotationA kinematic representation (convention) inherited from robotics

  • Z-axis aligned with joint

  • X-axis aligned with outgoing limb

  • Y-axis is orthogonal

  • Joints are numbered to represent hierarchy Ui-1 is parent of Ui

  • Parameter ai-1 is outgoinglimb length of joint Ui-1

  • Joint angle, qi, is rotation of xi-1 about zi-1 relative to xi

  • Link twist, ai-1, is the rotation of ith z-axis about xi-1-axis relative to z-axis of i-1th frame

  • Link offset, di-1, specifies the distance along the zi-1-axis (rotated by ai-1) of the ith frame from the i-1th x-axis to the ith x-axis

  • Inverse Kinematics (IK)Given end effector position, compute required joint anglesIn simple case, analytic solution existsUse trig, geometry, and algebra to solve

  • What is Inverse Kinematics?Forward Kinematics

  • What is Inverse Kinematics?Inverse Kinematics

  • What does look like?

  • Solution to Our example

    Number of equation : 2Unknown variables : 3

  • Redundancy System DOF > End Effector DOF

  • Analytic solution of 2-link inverse kinematics21a1a2O2O1O0x1x0x2y1y2y0(x,y)2

  • Failures of simple IKMultiple Solutions

  • Failures of simple IKInfinite solutions

  • Failures of simple IKSolutions may not exist

  • Iterative IK SolutionsFrequently analytic solution is infeasibleUse JacobianDerivative of function output relative to each of its inputs

    If y is function of three inputs and one output

    Represent Jacobian, J(X), as a 1x3 matrix of partial derivatives

  • JacobianIn another situation, end effector has 6 DOFs and robotic arm has 6 DOFsf(x1, , x6) = (x, y, z, r, p, y)Therefore J(X) = 6x6 matrix

  • JacobianRelates velocities in parameter space to velocities of outputs

    If we know Ycurrent and Ydesired, then we subtract to compute YdotInvert Jacobian and solve for Xdot

  • Turn to PDF slidesSlides from OBrien and ForsythCS 294-3: Computer Graphics Stanford Fall 2001

  • Differential KinematicsIs J always invertible? No!Remedy : Pseudo Inverse

  • Null spaceThe null space of J is the set of vectors which have no influence on the constraints

    The pseudoinverse provides an operator which projects any vector to the null space of J

  • Utility of Null SpaceThe null space can be used to reach secondary goals

    Or to find comfortable positions

  • Calculating Pseudo InverseSingular Value Decomposition

  • RedundancyA redundant system has infinite number of solutions

    Human skeleton has 70 DOFUltra-super redundant

    How to solve highly redundant system?

  • Redundancy Is BadMultiple choices for one goalWhat happens if we pick any of them?

  • Redundancy Is GoodWe can exploit redundancy

    Additional objectiveMinimal ChangeSimilarity to Given ExampleNaturalness

  • NaturalnessBased on observation of natural human posture Neurophysiological experiments

  • Conflict Between Goalsbaseee 2ee 1

  • Conflict Between Goalsbaseee 2ee 1Goal 1

  • Conflict Between Goalsbaseee 2Goal 2ee 1

  • Conflict Between Goalsbaseee 2ee 1Goal 1Goal 2

  • Conflict Between Goalsbaseee 2ee 1Goal 1Goal 2