人形机器人论文中英文资料对照外文翻译

Maio,D.

，和

Rizzi,S.

：校正航位推算错误地图建设

移动机器人

,I EEE cs Automat.17

（

1

）

（

2001

）

< br> ,37 - 47

。

Fusion Strategies for Minimizing Sensing-Level

Uncertainty in Manipulator Control

Abstract

：

Humanoid robotic applications require robot to act and

behave like human -ing soft computing like approach human

being

can

think,decide

and

control

himself

in

unstructured

dynamic

surroundings,where

a

great

degree

of

uncertainty

exists

in

the

information

obtained

through

sensory

the

robotics

domain

also,one of the key issues in extracting useful knowledge from sensory

data is that of coping with information as well as sensory uncertainty

at

various

this

paper

a

generalized

fusion

based

hybrid

classifier(ANN-FDD-FFA)has

been

developed

and

applied

for

validating

on

generated synthetic data from observation model as well as from real

hardware fusion goal,selected here,is primarily to minimize

uncertainties

in

robotic

manipulation

tasks

that

are

based

on

internal(joint

sensors)as

well

as

external(vision

camera)

sensory

effectiveness

of

present

methodology

has

been

extensively

studied

with

a

specially

configured

experimental

robot

having

five

degrees

of

freedom

and

a

simulated

model

of

a

vision

guided

the

present

investigation

main

uncertainty

handling

approach

includes

weighted

parameter

selection(of

geometric

fusion)by

a

trained neural network that is not available in standard manipulator

robotic

controller

approaches

in

hybrid

configuration

has

sig-nificantly

reduce

the

uncertainty

at

different

levels

for

faster

and

more accurate manipulator control as demonstrated here through rigorous

simulations and experimentations.

Key words

:sensor,fusion,FDD,FFA,ANN,

computing,manipulators,repeatability,accuracy ,covariance,matrix,uncer

tainty,uncertai nty ellipsoid.

uction

applic ations(industrial,military,scientific,medicine,wel fare,hous

ehold and amusement)are increasingly coming up with recent prog-ress in

which a robot has to operate in large and unstructured environment

[3,12,15].In most cases,the knowledge of how the surroundings are

changing

every

instant

is

fundamentally

important

for

an

optimal

control

of robot motions. Mobile robots also essentially have to navigate and

operate in very large unstruc-tured dynamic surroundings and deal with

significant uncertainty[1,9,19].When- ever a robot is operating in a

natural

nondeterministic

environment,there

always

exists

some

degree

of

uncertainty

in

the

conditions

under

which

a

given

job

will

be

conditions may,at times,vary while a given operation is being carried

major causes leading to the uncertainty are the discrepancies

arising in the robot motion parameters and in the various task-defining

amount

by

which

they

differ

from

those

called

for

in

the

process

specifications

may

not

always

be

deviations

may be due to inaccuracies in analytical design or in reproductions of

programmed motions or because of deterministic as well as random errors

in the algorithms,measurement data,data transmission links,and other

s in the status of the robot like instances of

malfunctions,failures,shift

in

the

frame

of

reference,etc.,also

lead

to

uncertainty in the operating conditions of the presence of

substantial uncertainty significantly affects the robot in the various

steps of sensing the state of a task;in adapting to the changes through

the control system;and in reasoning to select the actions needed to