2015_chapter_1

İTÜ-EEF Dept. Of Control Engineering

1KON 318E : Introduction to Robotics

Introduction to Robotics (KON 318E)

Autumn Semester

Hakan Temeltas , Prof.Dr.

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Weekly Lecture Plan

WeekTopic

1 Introduction

2 Rigid Motions

3 Homogeneous Transformations

4 Forward Kinematics

5 Inverse Kinematics

6 Differential Kinematics and Jacobians

7 MIDTERM EXAM I (27th Oct. 2015)

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Weekly Lecture Plan

WeekTopic

8 Differential Kinematics and Jacobians

9 Motion Planning

10 Trajectory Generation (or Mobile Robots)

11 Independent Join Control

12 MIDTERM EXAM II(1st Dec. 2015)

13 Robot Dynamics

14 Robot Sensors and Actuators

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Course Evaluation Criteria

Method Quantity Percentage(%)

Midterm Exams 2 40 (20+20)

Homework 3~4 10

Final Exam 1 50

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Condition : Studets MUST HAVE 20/100 minimum avarage point to take FINAL EXAM

ps : Studets can take Midterm Exam I OR II at end of the semester if they have a valid excuse



Text Books

Primary: Robot Modeling and Control, M. Spong, S. Hutchinson, and M. Vidyasagar, Wiley, 2006

Secondary:

Modeling and Control of Manipulators, L.Sciavicco, B. Siciliano, Springer, (6th printing), 2005

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Text Books

Secondary:

Introduction to Robotics: Mechanics and Control (3rd Edition), John J. Craig, Prentrice Hall, 2005

Secondary:

FUNDAMENTALS OF ROBOTICS(3rd Edition), Ming Xie, Series in Mach,ne Perception andArtificial Intelligence, World Scientific Books, 2010

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Introduction

• Historical perspective– The acclaimed Czech playwright Karel Capek (1890-

1938) made the first use of the word ‘robot’, from the Czech word for forced labor or serf.

– The use of the word Robot was introduced into his play R.U.R. (Rossum's Universal Robots) which opened in Prague in January 1921.

• Formal definition (Robot Institute of America):– "A reprogrammable, multifunctional manipulator

designed to move material, parts, tools, or specialized devices through various programmed motions for the performance of a variety of tasks".

Karel Capek

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Common applications• Industrial

– Robotic assembly

• Commercial– Household chores

• Military

• Medical– Robot-assisted surgery

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Common applications

• Planetary Exploration

– Fast, Cheap, and Out of Control

– Mars rover

• Undersea exploration

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Common applications• Biomimetic Robots : Using biological principles to

create new design ideas

MFI; Harvard & Berkeley

Lobster robt (from NortheasternRobotics)

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Common applications• Humanoid Robots : For robots to efficiently

interact with humans,

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Industrial robots• High precision and repetitive tasks

– Pick and place, painting, etc

• Hazardous environments

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• For the majority of this class, we will consider robotic manipulators as open or closed chains of links and joints

– Two types of joints: revolute (q) and prismatic (d)

Representations

(Type R) (Type P)

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Definitions

• End-effector/Tool– Device that is in direct contact with the environment. Usually very task-specific

• Configuration – Complete specification of every point on a manipulator

– set of all possible configurations is the configuration space

– For rigid links, it is sufficient to specify the configuration space by the joint angles

• State space– Current configuration (joint positions q) and velocities

• Work space– The reachable space the tool can achieve

• Reachable workspace

• Dextrous workspace

T

nqqqq ...21 q

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Common configurations: wrists

• Many manipulators will be a sequential chain of links and joints

forming the ‘arm’ with multiple DOFs concentrated at the ‘wrist’

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Example end-effector: Grippers

• Anthropomorphic or task-specific

– Force control v. position control

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Common configurations: elbow manipulator

• Anthropomorphic arm: ABB IRB1400

• Very similar to the lab arm (RRR)

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Common configurations: Stanford arm (RRP)

• Spherical manipulator (workspace forms a set of concentric

spheres)

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Common configurations: SCARA (RRP)

Adept Cobra Smart600 SCARA robot. symbolic diagram of Smart600 SCARA arm DOFs with axes of rotation/ranslation delineated

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Common configurations: cylindrical robot (RPP)

• workspace forms a cylinder

Symbolic diagram of RPP arm DOFs with axes of rotation/translation delineated Seiko RT3300 Robot (RPP arm)

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Common configurations: Cartesian robot (PPP)

• Increased structural rigidity, higher precision

– Pick and place operations

PPP arm DOFs with axes of translation delineated PPP arm (e.g., from Epson)

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Workspace: elbow manipulator

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Workspace comparison

(a) spherical

(b) SCARA

(c) cylindrical

(d) Cartesian

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Parallel manipulators

6DOF Stewart platform

• some of the links will form a closed chain with ground

• Advantages:

– Motors can be proximal: less powerful, higher bandwidth, easier to control

• Disadvantages:

– Generally less motion, kinematics can be challenging

ABB IRB940

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Simple example: control of a 2DOF planar manipulator

• Move from ‘home’ position and follow the path AB with a constant contact force F

all using visual feedback

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Coordinate frames & forward kinematics

• Three coordinate frames:

• Positions:

• Orientation of the tool frame:0 1

2

11

11

1

1

sin

cos

q

q

a

a

y

x

ty

x

aa

aa

y

x

21211

21211

2

2

sinsin

coscos

qqq

qqq

0 1 2

)cos()sin(

)sin()cos(

ˆˆˆˆ

ˆˆˆˆ

2121

2121

0202

02020

2qqqq

qqqq

yyyx

xyxxR

1

0ˆ

0

1ˆ

00 yx ,

)cos(

)sin(ˆ

)sin(

)cos(ˆ

21

21

2

21

21

2qq

qq

qq

qqyx ,

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Inverse kinematics

• Find the joint angles for a desired tool position

• Two solutions!: elbow up and elbow down

2

2

21

2

2

2

1

22

2 1)sin(2

)cos( DDaa

aayx tt

qq

D

D21

2

1tanq

)cos(

)sin(tantan

221

2211

1q

qq

aa

a

x

y

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Path planning

• In general, move tool from position A to position B while avoiding

singularities and collisions

– This generates a path in the work space which can be used to solve for joint

angles as a function of time (usually polynomials)

– Many methods: e.g. potential fields

• Can apply to mobile agents or a manipulator configuration

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system dynamics

Joint control

• Once a path is generated, we can create a desired tool path/velocity

– Use inverse kinematics and Jacobian to create desired joint trajectories

measured trajectory (w/ sensor noise)

error controller

actual trajectory

desired trajectory

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Other control methods

• Force control or impedance control (or a hybrid of both)

– Requires force/torque sensor on the end-effector

• Visual servoing

– Using visual cues to attain local or global pose information

• Common controller architectures:

– PID

– Adaptive

– Repetitive

• Challenges:

– Underactuation

– Nonholonomy (mobile agents)

– nonlinearity

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Sensors and actuators

• sensors

– Motor encoders (internal)

– Inertial Measurement Units

– Vision (external)

– Contact and force sensors

• motors/actuators

– Electromagnetic

– Pneumatic/hydraulic

– electroactive

• Electrostatic

• Piezoelectric

Basic quantities for

both:

• Bandwidth

• Dynamic range

• sensitivity

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Next class…

• Rigid Motions and Homogeneous transforms as the basis for forward and inverse kinematics

have any questions or concerns!

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Documents

2015_chapter_1