Humanoid Robot Development of a simulation environment of an entertainment humanoid robot Lisboa-September-2007 Pedro Daniel Dinis Teodoro Orientador:

Humanoid Robot Development of a simulation

environment of an entertainment humanoid robot

Lisboa-September-2007

Pedro Daniel Dinis Teodoro

Orientador: Professor Miguel Afonso Dias de Ayala Botto

Co-orientador: Professor Jorge Manuel Mateus Martins

2

Guide

Introduction

Set UpIndentificati

onSimulatorControlResultsConclusionsVideo

GoalGoal State of Art

Objectives

This thesis was developed in collaboration with Robosavvy Ltd and boosted the creation of the Humanoid Robotics Laboratory of IDMEC-Center of Intelligent Systems, at Instituto Superior Técnico (http://humanoids.dem.ist.utl.pt/ ).

The creation of the strong foundations for future developments in humanoid robots.

3

GoalGoal

Current commercially available humanoid robots are designed to perform motions using open-loop control.

These robots are usually not able to move on uneven terrain and it is difficult or impossible to get them to perform movements that require instantaneous reaction to momentary instability.

State of Art

Objectives

Guide

Introduction

Set UpIndentificati


4

1. The establishment of a real-time protocol communication between the PC, using Matlab/Simulink® and the robot

2. The identification of internal and external properties of the humanoid robot.

GoalGoal State of Art

Objectives

Guide

Introduction

Set UpIndentificati

onSimulatorControlResultsConclusionsVideo 3. LQR implementation for

stabilizing the humanoid robot on a high bar.

5

The humanoid The humanoid robotrobot

Hardware Architecture

Software Architecture

Bioloid humanoid robot from Robotis.com

AX12+ Servo•1 MBps communication Speed.•Full feedback on Position (300o), Speed, DC current, Voltage and Temperature.•Can be set as an endless wheel.•High Torque servos (1Nm).

CM5 Controller

•the main controller of the humanoid. •57600 bps to receive/transmite data through servos and PC

Guide

IntroductionSet UpIndentificati


6




Humanoid control architecture

Guide



7




C-MEX S-function written in C to communicate with the CM-5 throughout UART (universal asynchronous receiver / transmitter).

C program for Atmega128 for completing the serial communication bridge.

We have now a way to identify the parameters of the humanoid models making online experiments.

Guide



8

Mechanical Mechanical PropertiesProperties

DC Servo Properties

DC Servo Identification

Mathematical Model

Close Loop PosOpen Loop

Speed

Measured signals

Schematic of joint and link for two different humanoid configurations.

Guide

IntroductionSet UpIndentifica

tionSimulatorControlResultsConclusionsVideo

9


DC Servo Properties


Mathematical Model


Speed

Measured signals

Possible internal block diagram control of the servos.

Guide



10


DC Servo Properties


Mathematical Model


Speed

Measured signals

Experiments suggest that the servos do not have internally any angular

velocity feedback control.

Servos have an internal feedback position control

loop

Guide



11


DC Servo Properties


Mathematical Model


Speed

Measured signals

Dead-zone effect due to stiction. In our case this was clearly quantified to be around 7-10% of the

full range.

Experiments show that the output estimated

velocity error is proportional to the

voltage supplied to the servo.

Guide



12


DC Servo Properties


Mathematical Model


Speed

Measured signals

The dynamic characteristics of the

servo are well captured by the BJ model.

Box Jenkins (2,1,2,1) was found to best

approximate the desired dynamical behavior of the

servo.

5544.0z469.1z

z06217.0TF

2

Guide



13

The humanoid The humanoid modelmodel

SimMechanics simulator

Virtual Reality animation

The humanoid is treated as a three body serial chain in an inverted pendulum configuration.

Guide



14




The system is underactuated, being the motion of the legs and torso prescribed in order to stabilize the full body of the humanoid above the high bar.

Guide



15




Parent-Child hierarchy

Guide



16

Equations of Equations of motionmotion

State-Space model

Linear Quadratic Regulator

kil

kilcl

and

cbiffq

qllmm

cbiffq

qllmC

mCh

qlmg

jimm

jiI

qlllmm

i

ii

cb

dcbd

n

ik

k

ib

k

ijic

cb

dcbdcbkij

cb

dcbd

n

ik

k

ib

k

ijc

cb

ddcbki

n

ijijii

a

bba

n

ik

k

aki

ijji

k

n

jk

k

ja

k

ib

k

ijjc

cb

dcbdcbakij

1),min(,sin

1),min(,sin

,

cos

,

,

cos

1),min(

1),min(

1),min(

2

1

),min(

1

11

1),min(

nnnnnnn

n

n

h

h

h

q

q

q

mmm

mmm

mmm

2

1

3

2

1

2

1

2

1

21

22221

11211

The equations of motion for a generic n-link

underactuated inverted pendulum deduced from the Euler-Lagrange equations.

Guide



17


State-Space model


l (mm) lc (mm) m (g) I (gcm2)Link 1 (Arms) 143.6 68.7 367.6 7890.7Link 2 (Torso) 115.8 57.5 981.5 32898.6Link 3 (Legs) 184.0 116.3 576.4 11328.0

in order to use linear control algorithms, the system dynamics is linearized, using a first order Taylor's

expansion at the vertical unstable equilibrium, q=[π/2,0,0]T and q =[0,0,0]T.

9566.6972635.467

2635.4677831.527

5517.972065.176

00

00

00

0008591.2159113.2303471.7

0000776.767777.3485857.81

0000028.08764.1172389.74

100000

010000

001000

B

A

BuAxx

321321 ,,,,,

2qqqqqqx

State-space vector

Physical properties

Guide



18


State-Space model


analyzing the zeros and poles of the system, it can be concluded that

system is a non-minimum phase one

Linear Quadratic Regulator was chosen, which provides a linear state feedback control

law for the system

xku TWothout

Angle compensatio

n

WithAngle

compensation

Guide



19

IdealIdeal servoservo

Servo Servo resolutioresolutio

nn

Gyro Gyro resolutioresolutio

nn

ServoServodead-dead-zonezoneGuide



20

AchievedAchieved ControlControl

This project has successfully achieved the creation of the strong foundations for future developments in humanoid robots.

Guide


onSimulatorControlResultsConclusion

sVideo

Recommendations

21

AchievedAchieved ControlControl Recommendations

LQR strategy was successfully applied in the stabilization of the humanoid on a high-bar although only in simulation and without the nonlinearities of the servos.

Guide



sVideo

22

AchievedAchieved ControlControl Recommendations

Guide



sVideo

23

Guide



Humanoid Robot Development of a simulation

environment of an entertainment humanoid robot

Lisboa-September-2007

Pedro Daniel Dinis Teodoro

Orientador: Professor Miguel Afonso Dias de Ayala Botto

Co-orientador: Professor Jorge Manuel Mateus Martins

Documents

Humanoid Robot Development of a simulation environment of an entertainment humanoid robot Lisboa-September-2007 Pedro Daniel Dinis Teodoro Orientador: