all teams overview: team:topics 1 overview chapter 1: from teleoperation to autonomy chapter 2: the...

All Teams Overview:

Team: Topics

1 •Overview•Chapter 1: From Teleoperation to Autonomy•Chapter 2: The Hierarchical Paradigm

2 •Chapter 3: Biological Foundations of the Reactive Paradigm•Chapter 4: The Reactive Paradigm•Chapter 5: Designing a Reactive Implementation

3 •Chapter 7: The Hybrid Deliberative/Reactive Paradigm

Team 1 Overview

Name: Presents section of Book:

Jorge Franco Introduction and Overview

Willmert Pereyra What is a robot and brief history 1.1 – 1.4.1

George Ragousis Robot Control and Operation 1.4.2 – 1.7

Sylvester Delano GPS Strips 2.1 – 2.2.3

Alexander Torres NHC NIST RCS 2.2.4 – 2.7

Introduction and Overview

Jorge Franco

Overview

• What is AI robotics– 3 major paradigms

• Ways in which intelligence is organized

• Architectures for paradigms– Coherent– Reusable

• Single/Team of robots

Implementations

What are Robots?

• Connotation/denotation – anthropomorphic

• Origins on January 25, 1921, Prague, Karel Capek’s play, R.U.R (Rossum’sRossum’s Universal Robots)

• Term derived from Czech word “robota”, loosely translated as menial worker.

– Attitude towards robot has disastrous consequences:» Moral of rather socialist story: “Work defines a

person”

• Shift from human-like servants made from biological parts to human-like servants made up of mechanical parts due to science fiction– Classics:

• Metropolis (1926), The Day the Earth Stood Still (1951), and Forbidden Planet (1956)

• Shift from human-like mechanical creatures to whatever shape gets the job done is due to reality

• Definition used in book: an intelligent robot is a mechanical creature which can function autonomously.

What are Robots? (cont’d)

What are Robotic Paradigms?• A paradigm is a philosophy or set of assumptions and/or

rules/techniques which characterize an approach to a class of problems

• Why know paradigms?– Key to successfully program a robot for an application– Interesting from historical perspective

• Issues that spawned one the shift from one paradigm to another• 3 kinds

– Hierarchical – Reactive– Hybrid deliberative/reactive

• Described in two ways– Relationship between 3 accepted primitives

• Sense, Act, Plan– Way that sensory data is processed and distributed through the system

Robot Paradigm Primitives(fig1.2 from book)

Robot Primitives

Input Output

Sense Sensor data Sensed information

Plan Information (Sensed and/or cognitive)

Directives

Act Sensed information/ directives

Actuator commands

Sensing Organization in Robot Paradigms

• Way Sensory data:– Processed– Distributed

• Local processing– Sensor information restricted to specific/dedicated

way for each robot function

• Global world model processing– All SI first processed into a global world model– Subsets of model distributed to other functions as

needed

Overview of the 3 Paradigmsfig.1.3 a.) Hierarchical, b.) Reactive, and c.) Hybrid

deliberative/reactive

a.

b.

c.

Hierarchical Paradigm

• 1967 – 1990 • Top down fashion – Heavy on planning• Introspective view

– However as Cognitive Psych. now know:• Not always good assessment of thought process.• Default schemas or behaviors

• Global world model– Hard and brittle

• Frame problem and closed world assumption

Another View of the Hierarchical Paradigm (fig.1.4 from book)

Robot Primitives

Input Output


Plan Sensed and/or cognitive information

Directives


Actuator commands

The Reactive Paradigm (fig.1.5 from book)

Robot Primitives

Input Output



Directives


Actuator commands

The Hybrid Deliberative/Reactive Paradigm (fig.1.6 from book)

Robot Primitives

Input Output

Plan Information (Sensed and/or cognitive)

Directives

Sense-Act(behaviors)

Sensor data Actuator commands

Representative Architectures

• Templates for an implementation• Examples of what each paradigm really means• According to Mataric: an architecture is a principled way

of organizing a control system, with constraints on the way the control problem can be solved

• Common components in robot architecture and rules of thumb for placing them together– IC car –paradigm – Each car manufacturer has its own architecture– The car manufacturers may have slight modification on their

architecture for sedans, convertibles, SUV’s,etc.

Set Criteria for the Evaluation of an Architecture

• Modularity

• Niche Targetability

• Portability

• Robustness

Layout of the Section

• Divided into 8 chapters– 1. define Robotics– 2. describes Hierarchical Paradigm and 2 architectures– 3. sets the stage for understanding the Reactive Paradigm and

the motivation that spawned it.– 4. Describes the Reactive Paradigm and popular architecture– 5. Provides guidelines and case studies on designing robot

behaviors– 6. Discusses simple sonar and computer vision processing

techniques– 7. Describes the Hybrid Deliberative-Reactive Paradigm– 8. Discusses how the principles of the 3 paradigms have been

transferred to team of robots

Sections 1.1 –1.4.1

Willmert Pereyra

Uses of Robots

• Dirty jobs.

• Dull jobs.

• Dangerous jobs.

Robotics Timeline

Planetary rovers

vision

manufacturing

AI robotics

Telesystems

Industrial manipulatorsTelemanipulators

1960 1970 1980 1990 2000

Old Movies About Robots

• Modern Times (Charlie Chaplin), 1936.

• Metropolis, 1927.

• Silent Running, 1972.

• The Phantom Menace, 1999.

Modern Times 1937

Metropolis 1927

Silent Running 1972

The Phantom Menace 1999

Approaches to Robotics

• Artificial Intelligence (AI).

• Engineering.

AI vs. Engineering

• AI:– Uses paradigms.– All actions are human-like.

• Engineering:– Does not use paradigms.– Actions performed are

mechanical.

Engineering Control Types

• Ballistic control:– The position, trajectory and velocity profiles

are computed once.

• Feedback control:– The error between the goal and current

position is noted by a sensor(s): a new trajectory and profile is computed and executed. Then modified in the next update.

AI Robotics Terms

• Intelligent Robot:– A mechanical creature which can function

autonomously.

• Paradigm:– A philosophy or set of assumptions and/or

techniques which characterize an approach to a class of problems.

AI Robotics Terms

• Luddites:– People who object to robots, or technology in

general.

• Artificial Intelligence (AI):– (1) Science of making machines act

intelligently. (2) The study of ideas that enable computers to be intelligent. (3) An attempt to make computers do things that at present people are better at.

AI Robotics Terms

• Teach pendant:– A device that enables the programmer to

guide the robot through the desired set of motions.

• Automatic Guided Vehicle (AGV):– A vehicle that knows where it is, can plan a

path from its current location to its goal destination and can avoid colliding with obstacles.

AI Robotics Terms

• Telepresence: – The reduction of cognitive fatigue and

simulator sickness by making the human-robot interface more natural: virtual reality.

• Telemanipulator:– Sophisticated mechanical linkage which

translates motions on one end of the mechanism to motions at the other end.

AI Robotics Terms

• Industrial manipulator:– A reprogrammable multifunctional mechanism

that is designed to move materials, parts, tools, or specialized devices.

• Black factory:– A factory that has no lights turned on because

there are no workers.

Architecture Evaluation Criteria

• Support for modularity: – Good software engineering principles?

• Niche targetability: – Works well for the intended application?

• Ease of portability: – Works for other applications or other robots?

• Robustness: – Is the system vulnerable? Where?

Model S Telemanipulator

Movemaster Robot

Industrial Robots

Robotic Paradigms

1. Hierarchical.

2. Reactive.

3. Deliberative/Reactive.

Defining Paradigm Assumptions

• By the relationship between the primitives.

• By the way sensor data is processed and distributed.

Global World Model Problems

• Constructing generic global world models is very hard due to the frame problem and the closed world assumption.

Global World Model Problems

• Frame problem:– Deals with the representation of real-world

situations in a way that is computationally tractable.

• Closed/Open world assumption:– States that the world model contains

everything the robot needs to know (Closed) and if it is violated the robot may not be able to function correctly.


• Oldest paradigm.

• Prevalent from 1967-1990.

• Robot operates top-down.

• Emphasizes planning.

• Assumes thought is introspective.

• A global model captures all sensing data.


Primitives Input Output



Directives


Actuator commands

Robot Control and Operation Section 1.4.2 – 1.7

George Ragousis

4 Ways to control and operate a robot

• 1. Remote control (RC)• 2. Tele-operation• 3. Semi-autonomous• 4. Autonomous (AI)

1. Remote control

– you control the robot– you can view the robot

and it’s relationship to the environment

– operator isn’t removed from scene, not very safe

– ex. radio controlled cars, bomb robots

Boxing RC robots

http://dealnews.com/artclick.html?103106,153738

2. Teleoperation

– you control the robot– you can only view the

environment through the robot’s eyes

– don’t have to figure out AI

2. Teleoperation

Display

Control

Sensor

Mobility

Effector

Power

Communi-cation

Local

Remote

LocalRemote

2. Teleoperation

is suitable for applications where…• the tasks are unstructured and not repetitive• the task workspace cannot be engineered to permit the

use of industrial manipulators• key portions of the task require dexterous manipulation,

especially hand-eye coordination, but not continuously • key portions of the task require object recognition or

situational awareness • the needs of the display technology do not exceed the

limitations of the communication link (bandwidth, time delays)

• the availability of trained personnel is not an issue

2. Teleoperation

Disadvantages…

• Cognitive fatigue, 100% guidance

• Simulator sickness

• communications bandwidth (telepresence)

• Time delays (Darkstar 1 – Darkspot 0)

3. Semi-autonomous

Portion of directions and commands is given to robot

2 flavors

Shared control Control trading step by step instructions commanding robot to do

something

to accomplish task but no within its abilities and allowing the

full guidance is required robot to get it done without interaction

4. Autonomous

• Auto – nomousauto = self

nomos = rule self-commanded

• space robotics• the need for autonomy• artificial intelligence (AI)

Teleoperation Vs Autonomous remote operation Vs self operation

• much more difficult to achieve• higher risk of misjudgment and

false actions from robot• no time delays in operation• independent

goal of autonomy and AI:

To mimic the capabilities of animals or humans sufficiently in order to survive for long periods with only simple instructions from earth.

• easy to achieve• human in control – small

chances of decision and judgment errors

• dexterous manipulations• critical decisions by human

(Mars Pathfinder accident)• Introduces time delays in

proportion with the distance between local & remote.

Artificial Intelligence

Seven areas

1. Knowledge representation – how am I me?

2. Understanding natural language (willing spirit – weak flesh)

3. Learning

4. Planning & problem solving

5. Inference – just take a decision

6. Search

7. Vision

Section 2.1 – 2.2.3

Sylvester Delano

Introduction to AI Robotics (Team ONE)

Chapter2 Section 2.1 -2.2.3 58

The Hierarchical Paradigm• Describe the Hierarchical Paradigm in terms of the

3 robot primitives and its organization of sensing

• Name and evaluate one representative Hierarchical architecture in terms of: support for modularity, niche targetability, ease of portability to other domains, robustness

• Understand precondition, closed world assumption, open world, frame problem

• List two advantages and disadvantages of the Hierarchical Paradigm

Organization-SPA-globalStrips-ShakeyRep. Arch.-evaluation-NHC-RCASummary



Organization

PLANSENSE ACT


World model:1. A priori rep2. Sensed info3. Cognitive



Stanford Research Institute● SRI is an independent, non-profit research institute

conducting client-sponsored research and development for government agencies, commercial businesses, foundations, and other organizations.

● SRI is well known for its innovations in communications and networks, computing, economic development and science and technology policy, education, energy and the environment, engineering systems, pharmaceuticals and health sciences, homeland security and national defence, and materials and structures.



Shakey• The first mobile

robot to be able to reason about its own actions, Shakey combined research in robotics, artificial vision, and natural language processing.

• Built by SRI (Stanford Research Institute) for DARPA 1967-9




Shakey(cont'd)

• Programming was primarily in LISP.

• Used Strips as main algorithm for controlling what to do



What is LISP(LIST Processing) ?

• A high-level programming language used for developing AI applications. Developed in 1960 by John McCarthy, its syntax and structure is very different from traditional programming languages. For example, there is no syntactic difference between data and instructions.

• LISP is available in both interpreter and compiler versions and can be modified and expanded by the programmer. Many varieties have been developed, including versions that perform calculations efficiently.



Strips: Means-ends analysis


INITIAL STATE: Tampa, Florida (0,0)

GOAL STATE: Stanford, California (1000,200)

Difference: 1020 miles

“Go to Stanford AI Lab”



Difference Table

d<=200 miles FLY

100<d<200 TRAIN

d<=100 DRIVE

Distance(difference)

mode of transportation(OPERATOR)

d<1 WALK


mode=difference_table(INITIAL STATE, GOAL STATE, difference)

1. Look up what to do: FLY2. Not at SAIL, so repeat3. Look up what to do: DRIVE



Preconditions

d<=200 miles FLY

100<d<200 TRAIN

d<=100 DRIVE (rental)

DRIVE (personal car)

difference OPERATOR

d<1 WALK


How do I know if I’m at the airport or at home?Now must keep up with the state of the world

at airport

at home

PRECONDITIONS



Maintaining State of the World:Add and Delete Lists

d<=200 miles

FLY

100<d<200

TRAIN


at airport

DRIVE (personal)

at home

distance OPERATOR PRE-CONDITIONS

d<1 WALK


at city Yat airport

at city Yat train station

ADD-LIST

at city X

at city X

DELETE-LIST



Class Exercise


d<=200 miles

FLY

100<d<200

TRAIN


at airport

DRIVE (personal)

at home

distance OPERATOR PRE-CONDITIONS

d<1 WALK

at city Yat airport

at city Yat train station

ADD-LIST

at city X

at city X

DELETE-LIST



Strips Summary

• Designer must set up– World model representation– Difference table with operators, preconditions, add & delete lists– Difference evaluator

• Strips assumes closed world– Closed world: world model contains everything needed for robot

(implication is that it doesn’t change)– Open world: world is dynamic and world model may not be

complete• Strips suffers from frame problem

– Frame problem: representation grows too large to reasonably operate over


Section 2.2.4 –2.7

Alexander Torres

Team One – HierarchySTRIPS Summary

• Designer must set up– World model representation– Difference table with operators, preconditions, add &

delete lists– Difference evaluator

• Strips assumes closed world– Closed world: world model contains everything needed

for robot (implication is that it doesn’t change)– Open world: world is dynamic and world model may not

be complete

• Strips suffers from frame problem– Frame problem: representation grows too large to

reasonably operate over

Team One – HierarchyClosed World Assumption and the Frame Problem

It is impractical for a programmer to come up with all possible reactions, conditions to all probable cases in the real world

The need to formally represent the world and then maintain every change about it is nonnutritive.

The axioms (facts) that would frame the world would quickly become too numerous for any realistic domain

A proposed solution was ABStrips which divided the problem into multiple layers of abstraction (this would mean solving problems with increasing levels of details)

Team One – HierarchyNested Hierarchical Controller (NHC)

Representative Architecture

Nested Hierarchical Controller (NHC) •SENSE•PLAN•ACT

The robot gathers observation from its sensors and combines that information with priori knowledge to create the World Model.From the World Model, the robot can PLAN what action it should take.


Representative Architecture

Planning for navigation consists of three step executed by

Mission Planner, Navigator, and Pilot

Each of these can access the World Model

The last step is the Pilot module generating specific actions for the robot to do.


The Benefits of the NHC are:

•Unlike STRIPS it interleaves planning and acting

•It can adapt to changes in its environment if necessary

The Disadvantages of NHC are:

•Planning Function is only appropriate for navigation tasks

Team One – HierarchyNIST REAL Time Control System RCS

Real-time Control System Architecture Created by Jim Albus

Best suited for semi-autonomous control

Based on NHC, RCS is developed as a guide for manufacturers who wish to add AI to their robots.

Sensory perception modules introduce a useful preprocessing step between the sensor and the fusion into a world model

The Value Judgment module simulates the plan to ensure they work.

Behavior Generation Module operates similar to the pilot with less focus on navigations.

Advantage

• Provides an ordering of the relationship between sensing, planning, and acting.

Disadvantages

• Planning, every update cycle the robot would have to update a global world model and do some type of planning.

• Sensing and action are disconnected. This doesn’t allow for reflexive reactions found in real life.

• Dependence on global world model is related to the frame problem. A simple task can becomes incredibly complicated to describe.

• Uncertainty in semantics, sensor noise and actuator errors.

Team One – HierarchyAdvantages and Disadvantages

• Predicate logic and recursion used by STRIPS favors languages such as LISP and PROLOG

• Although LISP and PROLOG do not have good real-time control properties, the alternative at the time was FORTRAN IV which did not support recursion

• Hierarchical Paradigm forces programming for specific tasks instead of object oriented tasks.

• NHC and RCS decomposition of a task is not modular in design

Team One – HierarchyProgramming Considerations

Team One – HierarchySummary

•Except for NIST Real-time Control Architecture, Hierarchical Paradigm has fallen out of favor for more biologically based systems of control.

•It has contributed concepts and terminology such as preconditions, closed/open world assumptions, and the frame problem

•It has the inherent property to allow an evolution of intelligence from semi-autonomous control to full autonomy.

all teams overview: team:topics 1 overview chapter 1: from teleoperation to autonomy chapter 2: the...

Documents

hierarchical paradigm

reactive paradigm chapter

system slide

needed slide

contd slide

robot paradigm primitives

overview chapter

overview jorge franco