Kinematics. Basilio Bona. Semester 1, DAUIN Politecnico di Torino. B. Bona (DAUIN) Kinematics Semester 1, / 15

Similar documents
Kinematics. Basilio Bona. Semester 1, DAUIN Politecnico di Torino. B. Bona (DAUIN) Kinematics Semester 1, / 15

Kinematics. Basilio Bona. October DAUIN - Politecnico di Torino. Basilio Bona (DAUIN - Politecnico di Torino) Kinematics October / 15

Dynamics. Basilio Bona. Semester 1, DAUIN Politecnico di Torino. B. Bona (DAUIN) Dynamics Semester 1, / 18

Generalized coordinates and constraints

Differential Kinematics

ROBOTICS 01PEEQW. Basilio Bona DAUIN Politecnico di Torino

Lecture 7: Kinematics: Velocity Kinematics - the Jacobian

Rigid body dynamics. Basilio Bona. DAUIN - Politecnico di Torino. October 2013

MSMS Basilio Bona DAUIN PoliTo

Homogeneous Coordinates

Lecture 37: Principal Axes, Translations, and Eulerian Angles

8 Velocity Kinematics

Nonholonomic Constraints Examples

, respectively to the inverse and the inverse differential problem. Check the correctness of the obtained results. Exercise 2 y P 2 P 1.

Minimal representations of orientation

Dynamics 12e. Copyright 2010 Pearson Education South Asia Pte Ltd. Chapter 20 3D Kinematics of a Rigid Body

Lecture 38: Equations of Rigid-Body Motion

Trajectory-tracking control of a planar 3-RRR parallel manipulator

Non-holonomic constraint example A unicycle

Lecture 38: Equations of Rigid-Body Motion

Matrices A brief introduction

Interpolated Rigid-Body Motions and Robotics

Mechanics Physics 151

Position and orientation of rigid bodies

Lecture 9: Modeling and motion models

Robot Control Basics CS 685

Rigid Manipulator Control

DIFFERENTIAL KINEMATICS. Geometric Jacobian. Analytical Jacobian. Kinematic singularities. Kinematic redundancy. Inverse differential kinematics

arxiv: v1 [math.ds] 18 Nov 2008

3 Space curvilinear motion, motion in non-inertial frames

Quaternions. Basilio Bona. Semester 1, DAUIN Politecnico di Torino. B. Bona (DAUIN) Quaternions Semester 1, / 40

Case Study: The Pelican Prototype Robot

ROBOTICS Laboratory Problem 02

Exercise 1b: Differential Kinematics of the ABB IRB 120

PART ONE DYNAMICS OF A SINGLE PARTICLE

ROBOTICS 01PEEQW. Basilio Bona DAUIN Politecnico di Torino

The Jacobian. Jesse van den Kieboom

Vectors in Three Dimensions and Transformations

Probabilistic Fundamentals in Robotics. DAUIN Politecnico di Torino July 2010

Lecture Note 7: Velocity Kinematics and Jacobian

Lecture Note 7: Velocity Kinematics and Jacobian

UAV Coordinate Frames and Rigid Body Dynamics

Ridig Body Motion Homogeneous Transformations

Motion in Three Dimensions

ROBOTICS: ADVANCED CONCEPTS & ANALYSIS

Lecture Note 5: Velocity of a Rigid Body

Introduction to Robotics

CE 530 Molecular Simulation

II. DIFFERENTIABLE MANIFOLDS. Washington Mio CENTER FOR APPLIED VISION AND IMAGING SCIENCES

Motion in Space. MATH 311, Calculus III. J. Robert Buchanan. Fall Department of Mathematics. J. Robert Buchanan Motion in Space

Integration of Constraint Equations in Problems of a Disc and a Ball Rolling on a Horizontal Plane

Technische Universität Berlin

MSMS Vectors and Matrices

Lecture Notes Multibody Dynamics B, wb1413

Three-Dimensional Biomechanical Analysis of Human Movement

Circular Motion Kinematics

DYNAMICS OF MACHINES

Statistical Mechanics Solution Set #1 Instructor: Rigoberto Hernandez MoSE 2100L, , (Dated: September 4, 2014)

Lecture Note 1: Background

Modelling and Control of Mechanical Systems: A Geometric Approach

DYNAMICS OF SERIAL ROBOTIC MANIPULATORS

In the presence of viscous damping, a more generalized form of the Lagrange s equation of motion can be written as

Circular motion. Aug. 22, 2017

Classical Mechanics. Luis Anchordoqui

Lesson Rigid Body Dynamics

Extremal Trajectories for Bounded Velocity Differential Drive Robots

Rotations about the coordinate axes are easy to define and work with. Rotation about the x axis by angle θ is. R x (θ) = 0 cos θ sin θ 0 sin θ cos θ

Hamiltonian. March 30, 2013

Date: 1 April (1) The only reference material you may use is one 8½x11 crib sheet and a calculator.

Variation Principle in Mechanics

Nonholonomic systems as restricted Euler-Lagrange systems

Rigid body simulation. Once we consider an object with spatial extent, particle system simulation is no longer sufficient

Date: 31 March (1) The only reference material you may use is one 8½x11 crib sheet and a calculator.

Localización Dinámica de Robots Móviles Basada en Filtrado de Kalman y Triangulación

Chapter 3 Numerical Methods

Rotation Matrices. Chapter 21

13 Path Planning Cubic Path P 2 P 1. θ 2

Robotics, Geometry and Control - Rigid body motion and geometry

Projective Bivector Parametrization of Isometries Part I: Rodrigues' Vector

Homogeneous Transformations

arxiv: v1 [cs.sy] 29 Aug 2017

Physics 200 Lecture 4. Integration. Lecture 4. Physics 200 Laboratory

Multibody simulation

An Investigation of the Four Vertex Theorem and its Converse

Consistent Triangulation for Mobile Robot Localization Using Discontinuous Angular Measurements

On the Observability and Self-Calibration of Visual-Inertial Navigation Systems

Artificial Intelligence & Neuro Cognitive Systems Fakultät für Informatik. Robot Dynamics. Dr.-Ing. John Nassour J.

Newtonian Mechanics. Chapter Classical space-time

Numerical Methods for Inverse Kinematics

Lecture IV: Time Discretization

Fact: Every matrix transformation is a linear transformation, and vice versa.

Introduction to Vector Calculus

Assignments VIII and IX, PHYS 301 (Classical Mechanics) Spring 2014 Due 3/21/14 at start of class

HW 6 Mathematics 503, Mathematical Modeling, CSUF, June 24, 2007

Solution Set Five. 2 Problem #2: The Pendulum of Doom Equation of Motion Simple Pendulum Limit Visualization...

Dynamics of Open Chains

Lecture Notes - Modeling of Mechanical Systems

Rough Plane Analysis. Contents

MCE/EEC 647/747: Robot Dynamics and Control. Lecture 2: Rigid Motions and Homogeneous Transformations

DYNAMICS OF PARALLEL MANIPULATOR

Transcription:

Kinematics Basilio Bona DAUIN Politecnico di Torino Semester 1, 2016-17 B. Bona (DAUIN) Kinematics Semester 1, 2016-17 1 / 15

Introduction The kinematic quantities used to represent a body frame are: position (of the origin) x, linear velocity ẋ, linear acceleration ẍ, orientation (of the frame) α, angular velocity ω, angular acceleration ω. With α one indicates the generic angular parameters associated to the body frame orientation, e.g., Euler or RPY angles. Other parametrizations are possible, but they are more complex to deal with. One must use ω for the angular velocity instead of the time derivative α of the orientation angles: in kinematic equations it is necessary to use the true angular velocity vector. Notice that ω is a physical vector while α has no physical meaning (what represents the sum α 1 + α 2?). If α is required, there are relations from ω to α and vice-versa. B. Bona (DAUIN) Kinematics Semester 1, 2016-17 2 / 15

Kinematics: position equations The motion equations are described by two vectorial equalities x(t) = g x (q(t),λ,t) α(t) = g α (q(t),λ,t) where λ is a vector of (usually constant) parameters that characterize the system from a geometrical, physical or structural point of view. If one uses the pose vector p(t) T = [ x T (t) α T (t) ] the direct position kinematic function is given by a nonlinear equation [ ] gx ( ) DPKF: p(t) = g(q(t),λ,t) where g( ) = g α ( ) and the inverse position kinematic function, is given by the inverse nonlinear relation IPKF: q(t) = g 1 (p(t),λ,t) This equation is in general much more difficult to solve, since it requires the inversion of nonlinear trigonometric functions. B. Bona (DAUIN) Kinematics Semester 1, 2016-17 3 / 15

Kinematics: velocity equations One can express both the linear velocities ẋ(t) and the angular velocities α(t) of the rigid body as functions of the generalized velocitie q(t), obtaining the direct linear velocity kinematic function ẋ(t) d dt g x(q(t),λ,t) = J L (q(t),λ,t) q(t)+ g x(q(t),λ,t) t and the direct angular velocity kinematic function α(t) d dt g α(q(t),λ,t) = J A (q(t),λ,t) q(t)+ g α(q(t),λ,t) t The derivative α is in general not equal to the angular velocity ω, as we will see below. B. Bona (DAUIN) Kinematics Semester 1, 2016-17 4 / 15

Kinematics: velocity equations The matrix J L is called the linear Jacobian matrix [ ] [J L ] = gxi (q(t),λ,t) ij q j (t) The matrix J A [ ] [J A ] = gαi (q(t),λ,t) ij q j (t) is called the angular Jacobian matrix B. Bona (DAUIN) Kinematics Semester 1, 2016-17 5 / 15

Kinematics: velocity equations When the above functions do not explicitly depend on time t, we obtain a simplified form ẋ(t) = J L (q(t),λ) q(t) or simply ẋ = J L (q) q and α(t) = J A (q(t),λ) q(t) or simply α = J A (q) q We observe that the two relations are linear in the velocities, since they are the product between the Jacobian matrices and the generalized velocities q i (t). We also observe that the Jacobian matrices are, in general, time varying, since they depend on the generalized coordinates q(t). B. Bona (DAUIN) Kinematics Semester 1, 2016-17 6 / 15

Kinematics: velocity equations Embedding ẋ and α in a single vector, we can write [ẋ(t) ] ṗ α (t) = or equivalently ṗ α(t) α (t) = [ ] v(t) α(t) The quantity ṗ takes the name of generalized velocity and is not a vector, since the time derivatives of the angular velocities are different from the components of the physical angular velocity vector ω. When we use the true geometrical angular velocity ω, we write [ ] [ ] ẋ(t) v(t) ṗ ω (t) = or equivalently ṗ ω(t) ω (t) = ω(t) this vector [ v(t) ω(t) ] T is also called a twist. B. Bona (DAUIN) Kinematics Semester 1, 2016-17 7 / 15

Kinematics: velocity equations We can now write in a compact form the kinematic function of the generalized velocities: ṗ(t) d g(q(t),λ,t) = J(q(t),λ)dq(t) + g(q(t),λ,t) dt dt t where the Jacobian J is a block matrix composed by J L and J A [ ] JL (q(t),λ) J(q(t),λ) = J A (q(t),λ) If the kinematic position function g does not explicitly depend on time, we can write ṗ(t) = J(q(t),λ) q(t) or simply ṗ = J q B. Bona (DAUIN) Kinematics Semester 1, 2016-17 8 / 15

Kinematics: velocity equations As we will detail below, when the generalized velocity is expressed using the angles derivative ṗ α, then ṗ α = J α q and when the generalized velocity is expressed using the angular velocity ṗ ω, then ṗ ω = J ω q B. Bona (DAUIN) Kinematics Semester 1, 2016-17 9 / 15

This relation can be inverted only when the Jacobian is non-singular, i.e., detj(q(t)) 0 In this case, if the kinematic equations do not depend on time, we have what we call the inverse velocity kinematic function q(t) = J(q(t),λ) 1 ṗ(t) or simply q = J 1 ṗ The Jacobian depends on the generalized coordinates q i (t), and it can become singular for particular values of these coordinates; we say in this case that we have a singular configuration or a kinematic singularity. The coordinates q sing that produce the singularity are called singular configurations detj(q sing ) = 0 The kinematic singularity problem is not treated in this course, but is very important in robotics. B. Bona (DAUIN) Kinematics Semester 1, 2016-17 10 / 15

Angular velocity transformations Euler angles If α(t) are the angular parameters (Euler angles, RPY angles, etc.), the analytical derivative α(t) is called analytical (angular) velocity. The analytical derivative α does not necessarily coincide with the physical angular velocity vector ω, and the second derivative α does not necessarily coincide with the physical angular acceleration vector ω. Let us assume that the orientation is described by the Euler angles α E = [ φ(t) θ(t) ψ(t) ] T ; the analytical angular velocity (Eulerian velocity) is then φ(t) α E (t) = θ(t) ψ(t) The Eulerian velocity α(t) is transformed into the geometrical (angular) velocity by the following relation ω(t) = b φ φ + b θ θ + b ψ ψ, B. Bona (DAUIN) Kinematics Semester 1, 2016-17 10 / 15

Angular velocity transformations Euler angles Where b φ = 0 0, b θ = cosφ(t) sinφ(t), b ψ = sinφ(t)sinθ(t) cosφ(t)sinθ(t) 1 0 cosθ(t) and we can define the transformation between α E (t) and ω(t) introducing a square matrix φ ω(t) = M E (t) θ = M E (t) α E (t) ψ The transformation matrix 0 cosφ sinφ M E (t) = 0 sinφ cosφ sinθ 1 0 cos θ is NOT a rotation matrix and depends only on φ(t) and θ(t). B. Bona (DAUIN) Kinematics Semester 1, 2016-17 11 / 15

Angular velocity transformations Euler angles When detm E (t) = sinθ = 0 the matrix is singular. The inverse is sinφ cosθ cosφ cosθ 1 sinθ sinθ E (t) = cosφ sinφ 0 sinφ cosφ 0 sinθ sinθ M 1 B. Bona (DAUIN) Kinematics Semester 1, 2016-17 12 / 15

Angular velocity transformations RPY angles For the RPY angles α RPY = [ θ x θ y θ z ] T we have where ω (t) = M RPY (t) α RPY (t) cosθ z cosθ y sinθ z 0 M RPY (t) = sinθ z cosθ y cosθ z 0 sinθ y 0 1 For small angles we can approximate c i 1, s i 0 obtaining M RPY I; in this case ω(t) α RPY (t). B. Bona (DAUIN) Kinematics Semester 1, 2016-17 13 / 15

Angular velocity transformations RPY angles When detm RPY (t) = cosθ y = 0 the matrix is singular. The inverse is RPY (t) = M 1 cosθ z sinθ z 0 cosθ y cosθ y sinθ z cosθ z 0 cosθ z sinθ y cosθ y sinθ z sinθ y cosθ y 1 B. Bona (DAUIN) Kinematics Semester 1, 2016-17 14 / 15

Analytical and Geometrical Jacobians According to the type of angle related velocity, we have two types of angular Jacobians. If we use α, then If we use ω, then J α is called the Analytical Jacobian. J ω is called the Geometrical Jacobian. α = J α q (1) ω = J ω q (2) The relation between the two Jacobians is given by a linear transformation J ω = M(q)J α (3) where M = M E or M = M RPY B. Bona (DAUIN) Kinematics Semester 1, 2016-17 15 / 15