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Transcript
EE788:
Robot Cognition and Planning
Fall, 2009
Jong-Hwan Kim, Professor
Robot Intelligence Technology Lab.
EE, KAIST
http://rit.kaist.ac.kr
1
Course Overview
• Is a survey course, not a programming class,
though programming is required
• Focuses on paradigms and general AI software
architectures for expressing those paradigms
• Existing AI algorithms or best-practices for specific
functionality
• By end of course should understand:
– How DARPA Grand Challenge leader Team Red works
and why no one won
– How the Mars Exploratory Rovers and Global Hawk work
– How a Roomba works
– How a Sony Aibo works
Slides for this course are from Professor Robin Murphy, author of the textbook, Introduction
to AI Robotics, the MIT press.
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
2
1
What are Robots?
• Objectives
– Define Intelligent Robot
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Be able to list the four modalities of autonomous (unmanned)
vehicles and the five components common to all autonomous
systems
– Be able to describe at least two differences between AI and
Engineering approaches to robotics
– Define and describe the difference between automation and
autonomy
– List the seven areas of Artificial Intelligence
– List the three primitives of robot paradigms and express the three
paradigms of robotics in terms of these primitives
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
3
1
Intelligent Robot
• Mechanical creature which can function
autonomously
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Mechanical = built, constructed
– Creature = think of it as an entity with its own
motivation, decision making processes
– Function autonomously = can sense, act, maybe
even reason; doesn’t just do the same thing over
and over like automation
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
4
1
Why Robots?
Dirty, Dangerous, Dull Tasks
• JV2010, TRADOC, JFCOM, all branches even down to the
organic level
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Reconnaissance, MOUT, denial of area, consequence
management, logistics, demining
REPLACE WITH ROOMBA
www.roomba.com
Replace Humans with Robots
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
5
1
Why Robots?
Better Than Bio
• Robots at WTC…
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– voids smaller than person
could enter
– voids on fire or oxygen
depleted
Void:1’x2.5’x60’
• NBC Response
– Lose ½ cognitive attention
with each level of
protection
• Level A=12.5% of normal
ability
Do Things that Living Things Can’t
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
Void on fire
6
1
4 Major Robot Modalities
•
Unmanned Ground Vehicles
– since 1967
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
•
Unmanned Aerial Vehicles
– drones since Vietnam: Global Hawk, UCAV
•
Unmanned Underwater Vehicles or Autonomous Underwater Vehicles
– ROVs since 1960s
•
Unmanned Surface Vehicles
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
7
1
All Have 5 Common Components
• Mobility: legs, arms, neck, wrists
– Platform, also called “effectors”
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
• Perception: eyes, ears, nose, smell, touch
– Sensors and sensing
• Control: central nervous system
– Inner loop and outer loop; layers of the brain
• Power: food and digestive system
• Communications: voice, gestures, hearing
– How does it communicate (I/O, wireless, expressions)
– What does it say?
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
8
1
Unmanned Ground Vehicles
• Three categories:
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Mobile
– Humanoid/animal
– Motes
• Famous examples
–
–
–
–
–
DARPA Grand Challenge
NASA MER
Roomba
Honda P3, Sony Asimo
Sony Aibo
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
9
1
Taxonomy of Mobile Robots
Ground
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
Humanoid,
Animals
Man-packable
Mobile
Man-portable
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
Motes
Maxi
10
1
Unmanned Aerial Vehicles
• Three categories:
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Fixed wing
– VTOL
– Micro aerial vehicle (MAV),
which can be either fixed
wing or VTOL
• Famous examples
– Global Hawk
– Predator
– UCAV
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
11
1
Autonomous Underwater Vehicles
• Categories
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Remotely operated
vehicles (ROVs), which are
tethered
– Autonomous underwater
vehicles, which are free
swimming
• Examples
– Persephone
– Jason (Titanic)
– Hugin
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
12
1
Unmanned Surface Vehicles
• Categories
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Air-breathing submersible
– Jet-ski based
– Rigid Inflatable Boat based
• Examples
– USV-S
– OWL
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
13
1
Why UVs Need AI
•
Sensor interpretation
– Bush or Big Rock?, Symbol-ground problem, Terrain interpretation
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
•
Situation awareness/ Big Picture
•
Human-robot interaction
•
“Open world” and multiple fault diagnosis and recovery
•
Localization in sparse areas when GPS goes out
•
Handling uncertainty
•
Manipulators
•
Learning
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
14
1
7 Major Areas of AI
1. Knowledge representation
•
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
how should the robot represent itself, its task, and the world
2. Understanding natural language
3. Learning
4. Planning and problem solving
•
Mission, task, path planning
5. Inference
•
Generating an answer when there isn’t complete information
6. Search
•
Finding answers in a knowledge base, finding objects in the
world
7. Vision
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
15
Intelligence and the CNS
“Upper brain” or cortex
Reasoning over information about goals
“Middle brain”
Converting sensor data into information
Spinal Cord and “lower brain”
Skills and responses
1
Engineering Approach
• Comes out of manipulator, control-theoretic tradition
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
• Focus on platform, inner loop control laws
– Nerves, spinal cord, proprioceptive feedback
– Accurate model of physics of the situation
– How to perform an action versus why to do it
• Examples
– Robot arms, factory automation
– Auto-pilot, drones
– Humanoid robots
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
17
1
Industrial Robots
• Industrial robots (manipulators) aren’t
physically situated agents
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– high repetition in a world where everything is
fixtured to be in the right place at the right time
– focus on control theory, joint movement to get
fastest, repeatable trajectory
– only recently begun adding sensors to reduce need
for fixturing
• fixed lighting
• many cases cheaper just to shake the parts and sort
them into the right position for a standard
manipulator
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
18
1
Engineering Approach
Industrial Manipulators
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
• “Tommy” type of robots: deaf, dumb, and blind
• High precision, fast repetition
• Usually no sensing of the environment
– Welding can be off by an inch…
• AUTOMATION
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
19
1
Automation? Autonomy?
• Automation
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Execution of precise, repetitious
actions or sequence in controlled or
well-understood environment
– Pre-programmed
– Fly-by-wire is a type of automation
• Detailed models of physics and
environment
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
20
1
AI Focuses on Autonomy
• Automation
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Execution of precise, repetitious actions or sequence in
controlled or well-understood environment
– Pre-programmed
• Autonomy
– Generation and execution of actions to meet a goal or
carry out a mission, execution may be confounded by
the occurrence of unmodeled events or environments,
requiring the system to dynamically adapt and replan.
– Adaptive
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
21
1
So How Does Autonomy Work?
• In two layers
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
– Reactive
– Deliberative
• 3 paradigms which specify what goes in what layer
– Paradigm: a philosophy or set of assumptions and/or
techniques which characterize an approach to a class of
problems.
– Three paradigms for organizing intelligence in robots:
Hierarchical, reactive, hybrid deliberative/reactive.
– Paradigms are based on 3 robot primitives: sense, plan, act
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
22
1
AI Primitives within an Agent
SENSE
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
PLAN
ACT
LEARN
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
23
1
Hierarchical (1967)
SENSE
PLAN
ACT
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
1
2
3
Control people hated because
didn’t “close the loop”
AI people hated because
monolithic
Users hated because very slow
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
24
Reactive aka Behavioral (1986)
SENSE
ACT
PLAN
SENSE
ACT
SENSE
ACT
SENSE-ACT
couplings are
“behaviors”
Behaviors are independent,
run in parallel
1
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
Reactive
SENSE
ACT
SENSE
ACT
SENSE
ACT
PLAN
Users loved it because it worked
AI people loved it, but wanted
to put PLAN back in
Control people hated it because
couldn’t rigorously prove it
worked
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
26
1
Hybrid Deliberative/Reactive (1990)
• The robot first plans how to best decompose a task into subtasks
and then what are the suitable behaviors to accomplish each subtask
• Sensor data gets routed to each behavior and also the planner
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
PLAN
SENSE
SENSE
SENSE
ACT
ACT
ACT
Plan, then sense-act until task is complete or need to change;
Note movement towards event-driven planning rather than continuous
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
27
1
Hybrid
PLAN
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
SENSE
SENSE
SENSE
ACT
ACT
ACT
Control people hated it
because of AI, but are getting
over it
AI people loved it
Users loved it
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
28
1
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
sense
How AI Relates to Control Theory
World
plan
model
act
sense
sense
act
act
Reactive (fly-by-wire, inner loop control):
• Many concurrent stimulus-response behaviors,
strung together with simple scripting with FSA
• Action is generated by sensed or internal stimulus
• No awareness, no monitoring
• Models are of the vehicle, not the “larger” world
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
29
1
How AI Relates to Factory Automation
Deliberative:
monitoring
generating
• Upper level is mission generation & monitoring
• But World Modeling & Monitoring is hard (SA)
implementing
• Lower level is selection of behaviors to accomplish
task (implementation) & local monitoring
World
plan
model
selecting
sense
act
sense
sense
act
act
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
30
1
But…Theory-Practice Gap
We don’t know how to do this…
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
monitoring
generating
World
plan
model
selecting
sense
implementing
act
sense
sense
act
act
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
31
generating
World
model
plan
selecting
act
sense
sense
act
act
Reasoning over information about goals:
• Promising results: Navigation, payload planning,
contingency replanning
• Open issues: Multi-agent replanning, fault recovery &
reconfiguration, reasoning over multiple failures
Converting sensor data into information:
• Promising results: ATR, single failure health monitoring
• Open issues: creation of world models & situation
awareness, monitoring & detection of new threats,
exceptions, opportunities
Skills and responses
REACTION:
FLIGHT CONTROL
sense
implementing
DELIBERATION:
MISSION MANAGMENT
monitoring
1
Summary
• Robots mean more than just Sony dogs and Mars Rovers: land,
air, sea, and underwater
Definition
Motivation
Modalities
Intelligence
-Biological
-Engineering
-AI
-Paradigms
Summary
• Automation assumes a “closed world” while autonomy
assumes a “open world” which can change unexpectedly
• Engineering approaches focus on how to execute an action,
AI approaches focus on why to perform the action at that
particular time.
• Control Theory and AI is currently pretty good with “low level”
or “muscle” intelligence
• AI can outperform humans in planning, optimization, etc.
• AI isn’t good at converting sensing into information or
incorporating learning
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
33
1
Review Questions
• What is an Intelligent Robot?
• What are two reasons to have robots?
• What are the four modalities of autonomous (unmanned)
vehicles?
• What are the five components common to all autonomous
systems?
• What are two differences between AI and Engineering
approaches to robotics?
• What is the difference between automation and autonomy?
• What is the state of the practice?
• What are the seven areas of Artificial Intelligence?
• What are the three primitives of robot paradigms?
• What are the three paradigms of robotics in terms of these
primitives?
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
34
1
Glossary
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
3 D’s of robotics
Act
AI
Automation
Autonomous underwater vehicle
Autonomy
Closed world
Intelligent robot
Micro aerial vehicle
Mote
NBC
Open world
Paradigm
Plan
Sense
Unmanned aerial vehicle
Unmanned ground vehicle
Unmanned surface vehicle
Unmanned underwater vehicle
World model (part of plan robot primitive)
Introduction to AI Robotics R. Murphy (MIT Press 2000) for second edition
35