robotic chapter 8. artificial intelligencechapter 72 robotic 1) robotics is the intelligent...

Robotic

Chapter 8

Artificial Intelligence Chapter 72

Robotic 1) Robotics is the intelligent connection of perception

action.2) A robotic is anything that is surprisingly (moving

target) animate.3) perceptual (S/W) + motor task (H/W) [action]• operate in the real world : searching and

backtracking can be costly• we need operating in a simulate world with full

information for an optimal plan by best-first search• we can checked preconditions of the operators

using perception to perform action• real time search : p. 562 A* algorithm, RTA* (Korf

1988)


Vision

2D 3Dsignal processing : enhance the imagemeasurement analysis : for image containing a

single object determining the 2D extent of the object depicted

pattern recognition : for single object images, classify the object into category

image understanding : for image containing many objects in the image, classify them, build 3D model of the scene. see Figure 14.8 p. 367


• Problem :• ambiguous image : see Figure 21.2 p. 564• Figure 21.3 p. 565 using low level knowledge to

interpret an image• image factor, sensor fusion : color, reflectance,

shading• Figure 21.4 p. 565 using high level knowledge to

interpret an image (a) use surroundings objects to help (b) baseball, log in a fireplace, amoeba, [egg, bacon, and plate]

• Figure 21.5 p. 567 Image understanding• analog signal Image 2D features

3D features• 3D composite objects

Object identification

Vision


Speech Recognition• speaker dependence (we can train the system) /

speaker independence• continuous / isolated word speech• real time SPHINX (1988) / offline processing • large (difficult) / small vocabulary • broad (difficult) / narrow grammar: TANGORA

(1985) 20000 words vocabulary• HMM (Hidden Markov Modeling) SPHINX system

– statistical learning method– HMM is a collection of states and transitions


Speech RecognitionHMM (Hidden Markov Modeling) SPHINX

system statistical learning method

HMM is a collection of states and transitionsthe problem of decoding a speech waveform turns

into the problem of finding the most likely path (set of transitions) through an

appropriate KMM.


Action• p. 569 : navigation around the world

• planning routes / path planning• reaching desired destinations without bumping

into things• see Figure 21.6–21.9 p. 570-571

• constructing a visibility graph

• configuration space / C-space (Lozano-Perez 1984)

– basic idea is to reduce the robot to a point P and do path planning in an artificially constructed space

– rotation (X,Y,)

• obstacles can be transformed into 3D C-space objects, visibility graph can be created and

searched.


Manipulation

• end-effectors (two-gripper) / a human like hand

• pick-and-place : grasp and object and move it to a specific location see Figure

21.10-21.11 p. 572-573• Figure 21.11-21.12 (a) naive strategy for grasping

and placement• Figure 21.11-21.12 (b) clever strategy for

grasping and placement• planning p. 332 e.g. Block world ON(A,B)

HOLDING , ARMEMPTY


Manipulation• planning p. 332 e.g. Block world ON(A,B)

HOLDING , ARMEMPTY• Components of a planning system

1) choose the best rule to apply2) applying rules see Figure 13.2-13.3 p. 336-3373) detecting a solution4) detecting dead ends5) repairing an almost correct solution


The End

robotic chapter 8. artificial intelligencechapter 72 robotic 1) robotics is the intelligent...

Documents

artificial intelligencechapter

image image factor

ambiguous image

d features

analog signal image

category image understanding

d cspace objects

d extent