Outline: Introduction Solvability Manipulator subspace when n<6

Slides:



Advertisements
Similar presentations
ME 4135 Robotics & Control R. Lindeke, Ph. D.. FKS vs. IKS  In FKS we built a tool for finding end frame geometry from Given Joint data:  In IKS we.
Advertisements

ROBOT VISION Lesson 9: Robot Kinematics Matthias Rüther
Inverse Kinematics Professor Nicola Ferrier ME 2246,
Outline: Introduction Link Description Link-Connection Description
Links and Joints.
Inverse Kinematics Course site:
Introduction University of Bridgeport 1 Introduction to ROBOTICS.
Outline: Introduction Solvability Manipulator subspace when n<6
Manipulator’s Inverse kinematics
Review: Homogeneous Transformations
Forward and Inverse Kinematics CSE 3541 Matt Boggus.
Trajectory Generation
Inverse Kinematics Set goal configuration of end effector
CSCE 641: Forward kinematics and inverse kinematics Jinxiang Chai.
Inverse Kinematics Problem:
Time to Derive Kinematics Model of the Robotic Arm
CSCE 641: Forward kinematics and inverse kinematics Jinxiang Chai.
Ch. 3: Forward and Inverse Kinematics
IK: Choose these angles!
Ch. 3: Forward and Inverse Kinematics
Inverse Kinematics How do I put my hand here? IK: Choose these angles!
Introduction to ROBOTICS
CSCE 689: Forward Kinematics and Inverse Kinematics
Chapter 5: Path Planning Hadi Moradi. Motivation Need to choose a path for the end effector that avoids collisions and singularities Collisions are easy.
Introduction to ROBOTICS
Inverse Kinematics Jacobian Matrix Trajectory Planning
An Introduction to Robot Kinematics
INTRODUCTION TO DYNAMICS ANALYSIS OF ROBOTS (Part 5)
Goal Directed Design of Serial Robotic Manipulators
Advanced Graphics (and Animation) Spring 2002
Definition of an Industrial Robot
Dimensional Synthesis of RPC Serial Robots
Inverse Kinematics Kris Hauser
Lecture 2: Introduction to Concepts in Robotics
Chapter 2 Robot Kinematics: Position Analysis
Inverse Kinematics Find the required joint angles to place the robot at a given location Places the frame {T} at a point relative to the frame {S} Often.
INVERSE KINEMATICS ANALYSIS TRAJECTORY PLANNING FOR A ROBOT ARM Proceedings of th Asian Control Conference Kaohsiung, Taiwan, May 15-18, 2011 Guo-Shing.
Outline: 5.1 INTRODUCTION
Chapter 5 Trajectory Planning 5.1 INTRODUCTION In this chapters …….  Path and trajectory planning means the way that a robot is moved from one location.
Manipulator’s Forward kinematics
CSCE 441: Computer Graphics Forward/Inverse kinematics Jinxiang Chai.
Chapter 7: Trajectory Generation Faculty of Engineering - Mechanical Engineering Department ROBOTICS Outline: 1.
Kinematics. The function of a robot is to manipulate objects in its workspace. To manipulate objects means to cause them to move in a desired way (as.
Chapter 2: Description of position and orientation Faculty of Engineering - Mechanical Engineering Department ROBOTICS Outline: Introduction. Descriptions:
CSCE 441: Computer Graphics Forward/Inverse kinematics Jinxiang Chai.
COMP322/S2000/L111 Inverse Kinematics Given the tool configuration (orientation R w and position p w ) in the world coordinate within the work envelope,
MECH572A Introduction To Robotics Lecture 5 Dept. Of Mechanical Engineering.
MT411 Robotic Engineering Asian Institution of Technology (AIT) Chapter 2 Introduction to Robotic System Narong Aphiratsakun, D.Eng.
MT411 Robotic Engineering Asian Institution of Technology (AIT) Chapter 5 Wrists and End Effectors Narong Aphiratsakun, D.Eng.
Manipulator Kinematics Treatment of motion without regard to the forces that cause it. Contents of lecture: vResume vDirect kinematics vDenavit-Hartenberg.
Robotics Chapter 3 – Forward Kinematics
Velocity Propagation Between Robot Links 3/4 Instructor: Jacob Rosen Advanced Robotic - MAE 263D - Department of Mechanical & Aerospace Engineering - UCLA.
CSCE 441: Computer Graphics Forward/Inverse kinematics
IK: Choose these angles!
IK: Choose these angles!
Trajectory Generation
Character Animation Forward and Inverse Kinematics
Inverse Manipulator Kinematics
INVERSE MANIPULATOR KINEMATICS
Direct Manipulator Kinematics
Direct Kinematic Model
Inverse Kinematics (Reza N. Jazar, Ch. 6)
Special English for Industrial Robot
CSCE 441: Computer Graphics Forward/Inverse kinematics
Chap 11 – Case Studies.
Inverse Kinematics 12/30/2018.
Inverse Kinematics Problem:
Outline: Introduction Solvability Manipulator subspace when n<6
Special English for Industrial Robot
Chapter 4 . Trajectory planning and Inverse kinematics
Presentation transcript:

Outline: Introduction Solvability Manipulator subspace when n<6 Algebraic vs. Geometric Example: Kinematics of PUMA Robot

Introduction: Direct kinematics: Given the joint angles  calculate the position and orientation of the tool {T} relative to the station {S} Inverse kinematics: Given the desired position and orientation of the tool {T} relative to the station {S}, how to calculate the set of joint angles that give the desired result? Find {W} from {T}; Find {B} from {S}; Solve for joint angles

Solvability: Nonlinear problem: solve to find the values of Linear and nonlinear problems? Ex.: Puma manipulator 12 values  find 12 equations and 6 unknowns, rotation part (r11 … r33), only 3 independent

Solvability: Nonlinear problem: solve to find the values of Linear and nonlinear problems? Ex.: Puma manipulator 12 values  find 12 equations and 6 unknowns, rotation part (r11 … r33), only 3 independent

Solvability:  3 independent equations for the orientation and 3 independent equations for the position Nonlinear equations that are difficult to solve. Note that these were for simple links α = 0, 90, -90, … and many (d & a) = 0. General case (α, d, & a) have other nonzero values More complex case. We must concern on Existence of solution? Multiple solutions? Method of solution?

Solvability: (Existence of solution) Existence or nonexistence of a solution defines the workspace of the manipulator. Workspace (W.S.): (Figure) The volume of the space that the E.E. of the robot can reach. A solution to exist  the desired position & orientation (goal) must lie in the W.S. Two types of workspaces: Dextrous W.S.: volume of the W.S. in which the E.E. can reach with all the orientations. Reachable W.S.: volume of the W.S. in which the E.E. can reach in at least one orientation.  Dextrous W.S. is a subset of the reachable W.S.

Solvability: (Existence of solution) Return

Solvability: (Existence of solution) Example: if l1 = l2 determine the dextrous and reachable W.S.

Solvability: (Existence of solution) Example: if l1 = (l2/2) determine the dextrous and reachable W.S.

Solvability: (Existence of solution) Factors that affect the W.S. of a robot: Limitations on joint angles Generally: min < θi < max. Most of the robots have limitations on their joint angles.  The W.S. is reduced; this may affect the attained positions or the number of orientations for the attained position. Ex.: for the previous sketch 0 ≤ θi ≤ 180 sketch the W.S.  The same positions can be reached, however in only one orientation. Limitations on the number of DoF: A 3D-space goal is not attainable by a manipulator of DoF < 6. For the manipulator of the previous example can not attain a position of nonzero z-value.

Solvability: (Multiple Solutions) The manipulator can reach the goal with different configurations. Ex. The planar 3DoF manipulator shown can reach any goal in the dextrous W.S. in more than one way.  (Problem) the system should be able to calculate all and choose one. A good choice can be based on minimizing the amount that each joint is required to move. Which is almost the same as choosing the solution “closest” to the current configuration. Must be investigated. (energy, path,…)

Solvability: (Multiple Solutions) The manipulator can reach the goal with different configurations. Ex. The planar 3DoF manipulator shown can reach any goal in the dextrous W.S. in more than one way.  (Problem) the system should be able to calculate all and choose one. In the case of the existence of an obstacle  the configuration free of obstacles is chosen.

Solvability: (Multiple Solutions) Factors that affect the number of solutions: The number of joints (DoF). the range of motion of the joint. DH parameters (ai, αi, θi, di): (the number of nonzero DH parameters ↑  the number of solutions ↑). Example: For a general 6 rotational joints robot there is a direct relation between # of nonzero ai and the # of solutions

Solvability: (Multiple Solutions) “For a completely general rotary-jointed manipulator with six degrees of freedom, there are up to sixteen solutions possible” Example: the Puma robot has 8 different solutions for general goals

Solvability: (Method of Solution) Recall: Nonlinear equations no direct method / algorithm for solving for a given position and orientation the algorithm can find all the sets of joint variables A manipulator is solvable Numerical methods are dismissed as they converge to local solution

Solvability: (Method of Solution) Two types of solutions: Closed form solutions Numerical solutions:

Solvability: (Method of Solution) Two types of solutions: Closed form solutions Numerical solutions: Iterative  much slower Need initial guess Converge to local solutions

Solvability: (Method of Solution) Two types of solutions: Closed form solutions Numerical solutions: Iterative  much slower Need initial guess Converge to local solutions Out of our scope

Solvability: (Method of Solution) Two types of solutions: Closed form solutions: Solution method based on analytic expressions or on the solution of four degrees polynomial or less (no need for iterative methods to reach a solution). all systems with revolute and prismatic joints having a total of a six DoF in a single series chain are now solvable (numerically). Analytical solution is for special cases only: Several intersecting joint axes Many i equal to zero or 90 Closed form solution for the robot is a very important designer objective!

Solvability: (Method of Solution) Two types of solutions: Closed form solutions: A condition for closed form solution of a six rev. joints robot is that three consecutive joint axes intersect at a point (most of the new robots). Pieper presented an approach for solving the inverse kinematic of a robot of such condition. See the book for more information.

The notion of a manipulator subspace (n<6) A manipulator that has # DoF<6 has a workspace lower than the workspace of a 6-DoF robot of the same topology, i.e. its workspace is a portion or a subspace of higher DoF robot. A 6-DoF workspace is a subset of space. A lower DoF robot workspace is a subset of its subspace. Which is also a subset of a 6-DoF robot subspace of the same topology.

The notion of a manipulator subspace (n<6) Example: The subspace of the two links robot is the plane (x,y), its W.S. is a subset of the plane: circle of radius L1+L2 (reachable)

The notion of a manipulator subspace (n<6) A way to specify the subspace of a robot is from the expression of its wrist/tool frame (position and orientation relative to the base frame) as a function of the variables of the robot. i.e. as a function of any independent parameters. Example: Find the subspace of the following robot, (x,y)

The notion of a manipulator subspace (n<6) Solution: This can be done in two ways: Find Then (x,y)

The notion of a manipulator subspace (n<6) Solution: Or, use (x,y,) to calculate , as follows, (x,y)

The notion of a manipulator subspace (n<6) Solution: Or, use (x,y,) to calculate , as follows, Any wrist frame that does not have the structure of lies outside the subspace of this robot  and so lies outside of its W.S. VERY IMPORTANT Only 3 ind. para. must appear in

The notion of a manipulator subspace (n<6) Example: Give the description of the subspace of for the following 2 three-link robot is a unit vector in the direction of (x,y)

The notion of a manipulator subspace (n<6) (x,y)

The notion of a manipulator subspace (n<6) 2-DoF  only 2 ind. parameters appear in the previous equation (x,y) (x,y)

Algebraic VS. Geometric Solutions Algebraic solution: (example 3-DoF robot) For this robot if (x, y, ) are known, then one can calculate Also from the DH parameters of this robot (x,y)

Algebraic VS. Geometric Solutions Algebraic solution: (example 3-DoF robot) For this robot if (x, y, ) are known, then one can calculate Also from the DH parameters of this robot (x,y)

Algebraic VS. Geometric Solutions Algebraic solution: (example 3-DoF robot) For this robot if (x, y, ) are known, then one can calculate Also from the DH parameters of this robot (x,y)

Algebraic VS. Geometric Solutions (Algebraic)  (x,y) Note that: Two possible solutions!

Algebraic VS. Geometric Solutions (Algebraic) Also, if we calculate and , and taking into account that: From which one can obtain that: 2 was already calculated Making use of the relation: ?

Algebraic VS. Geometric Solutions (Geometric) For a 3D robot decompose the spatial geometry of the arm into several plane geometry. Example: planner robot (simpler case) Notes!