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Transcript
The Role of Intelligent Robotics
in Teaching A.I.
PACISE 2007
March 24
Mark M. Jones
Oskars J. Rieksts
Overview
Motivation
 Reframing AI
 Main Areas of AI
 The Big 3 of Robotics
 Intelligent Mobile Agents – Issues
 AI Issues in Robotics
 Learning from Experience
 Conclusions

2007
Kutztown University
2
Motivation
– inherently interesting
 Attract students to CS
 Attract students to AI
 Undergrad research opportunities
 Fun
2007
Kutztown University
3
Reframing A.I.
{the textbooks}

Elaine Rich
 Artificial Intelligence
 Search, GPS, STRIPS

Russell & Norvig
 A.I. : A Modern Approach
 Intelligent agent

Robin Murphy
 An Introduction to AI Robotics
 Interactive applied A.I.
2007
Kutztown University
4
The Main Areas of AI
Knowledge Representation
 Inference and reasoning
 Learning
 Planning
 Natural language processing
 Search
 Vision

2007
Kutztown University
5
The Big 3 of Robotics
 Sense
 Plan
 Act
2007
Kutztown University
6
Intelligent Mobile Agents - Issues
Awareness
 Autonomy
 Mobility
 Knowledge
 Action
 Control
 Cooperation
 Communication

2007
Kutztown University
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Awareness

Sensing
 Situatedness
 The world
 Effect of actions
 Self

Knowing
 What
 Where
 How
 When
2007
Kutztown University
8
Autonomy
Purpose
 Direction
 Decision

2007
Kutztown University
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Mobility
Location
 Change
 Direction

2007
Kutztown University
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Action
Purpose
 Planning
 Decision
 Behavior

2007
Kutztown University
11
Control
Coordination
 Timing
 Knowledge

2007
Kutztown University
12
Cooperation
Human-robot cooperation
 Multi-robot cooperation
 Conscious coordination
 Emergent behavior

2007
Kutztown University
13
Communication
Human-robot communication
 Robot-robot communication
 Sub-cognitive communication
 Cognitive communication

2007
Kutztown University
14
AI Issues in Robotics
Spatial Cognition: A Case Study
2007
Kutztown University
15
Spatial Cognition

Definition:
 Cognitive functions that enable people to deal
effectively with spatial relations, visual spatial
tasks and orientation of objects in space.
 One aspect of these cognitive skills is spatial
orientation, which is the ability to orient oneself
in space relative to objects and events; and the
awareness of self-location (A.S. Reber, The
Penguin Dictionary of Psycology).
2007
Kutztown University
16
Early History


John Locke (1632 – 1704)
 Essay on Human Understanding
 Tabula rasa = blank slate
 Sensations strike blank mind
 Mental processes produce vision of the world
George Berkeley (1685 – 1753)
 Essay Toward a New Theory of Vision
Explored relationship between sight and touch . .
 and between ideas and the material world
2007
Kutztown University
17
20th Century
George M. Stratton (1865-1957)
 Experiments with vision

 Inversion of visual input (special goggles)
 Visual system builds anew
 Gregory: “perhaps the most famous experiment
in the whole of experimental psychology”

The Spatial Harmony of Touch and Sight
2007
Kutztown University
18
Stratton’s Experiment

Immediate consequence
 Perceptual-motor coordination disrupted
 Disparity between seen and thought to be

Restoration
 Day 3 – “things interconnected into a whole”
 Process – “piecing together parts of the ever-changing
visual fields”
 Visual system builds anew “growing from an isolated
group of perceptions”
 “correspondence, point by point, between touch and
sight, is built up associationally”

Conclusion
 by experience person learns “what visual position
corresponds to any given tactual position”
2007
Kutztown University
19
Cognitive Structuring

Rudolph Carnap
 Der logische Aufbau der Welt
 The Logical Structure of the World

Aufbau
 building
 setup
 structure
 superstructure

Structured artifact
2007
Kutztown University
20
Issues in Spatial Cognition

Experiential Space
 Ego-centric
 Goal-oriented
 Tight sensory-motor coupling
 Minimal knowledge representation

Rodney Brooks
 Intelligence without representation
Bickhard’s frog
 Kirsh’s Earwig

2007
Kutztown University
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Issues in Spatial Cognition

Arkin, Murphy, et. al.
 Cspace – configuration space
 Path planning – plan, then act
 A* search
 Minimal conceptualization

Problems
 Subgoal obsession
 Lost opportunities

Oliver Sacks
 The Man Who Mistook His Wife for a Hat
2007
Kutztown University
22
Issues in Spatial Cognition

Benjamin Kuipers
 Semantic Spatial Hierarchy
» Artificial Intelligence, 1999

Aspects
 Models human cognitive map
 Multiple interacting representations
 Both
» Qualitative
» Quantitative
 Multiple levels
2007
Kutztown University
23
Spatial Semantic Hierarchy - Levels

Control level
 Local geometric maps

Causal level
 Behavior
 States linked by actions

Topological level
 External ontology
» Places
» Paths
» Regions
 Explain observed causal level patterns
2007
Kutztown University
24
Issues in Spatial Cognition Navigation

Foo, Warren, Tarr
 Human spatial strategies

Task : learn novel shortcut
 Metric cognitive map
 Landmark-based navigation

Conclusions
 Landmark-based predominates
 Ants
» 1st use survey knowledge . .
» then switch
 People do not
2007
Kutztown University
25
Spatial Cognition – Study Centers

Transregional Collaborative Research Center
 Spatial Cognition: Reasoning, Action, Interaction
 Established by the Deutsche Forschungsgemeinschaft
(DFG)
 Universities of Bremen and Freiburg

Concerned with:
 Knowledge about spatial environments
» Acquisition
» Organization
» Utilization
» Revision
2007
Kutztown University
26
Spatial Cognition – Study Centers

Research Issues
 Investigatin of human spatial cognition
Mobile robot navigation

Goal
 Investigate cognitive foundations for humancentered spatial assistance systems.
2007
Kutztown University
27
Spatial Cognition – Study Centers

Spatial Cognition Priority Program
 Spatial behavior
 Spatial inference
 Spatial coding
 Aspect maps
 Ego space
 Mental models
 Robot navigation
 Route knowledge/learning
 Landmark usage
2007
Kutztown University
28
AI Issues in Robotics

Awareness
 Vision
 Sensor interpretation
 Knowledge acquisition
 Learning

Autonomy
 Cognitive basis
 Planning
 Decision
2007
Kutztown University
29
AI Issues in Robotics

Mobility
 Localization
 Mapping
» Spatial representation
Topological vs. metrical
 Egocentric vs. allocentric
 Semantic structure of space

» Spatial reasoning
» Experiential realization
 Path Planning
» Optimization
2007
Kutztown University
30
AI Issues in Robotics

Knowledge
 Knowledge representation
 Knowledge acquisition
 Learning
 Metaknowledge

Action
 Planning
 Decision
 Understanding
» Causality
» Consequences
2007
Kutztown University
31
AI Issues in Robotics

Control
 Control Paradigms
»
»
»
»
Supervisory
Reactive
Hybrid – deliberative/reactive
Role of autonomous control
 Coordination
» Sensing & acting
» Timing
2007
Kutztown University
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AI Issues in Robotics

Cooperation
 Awareness of others
 Shared goals
 Models of coordination
 Supervisory
 Teamwork
 Unaware cooperation

Communication
 Language
» Understanding
» Generation
2007
Kutztown University
33
Sample Projects
Simulated/Theoretical
Mapping
 Path planning

 Graph-based
 Limo driver
» Asymmetric TSP
 Delivery robot
Emergent behavior – flocking
 Simulator construction

2007
Kutztown University
34
Sample Projects – Real World
From scratch
 Roomba-based

 RooTooth
 On-board processor {API}

Create-based
 Heat-seeking
 Odor interpretation
Rehabilitative assistant
 Robotics Tutorial - Robotut

2007
Kutztown University
35
Learning from Experience

Simulators
 OS issues
 Library incompatibilities
 Poor documentation
 Wasted time

Hardware
 Basic electronics
 Component failure
 Possible quagmire
2007
Kutztown University
36
Key Lessons

Maintain
 Primacy of theoretical
 Clear goal

Find
 Tested hardware
 Good text

Texts
 Murphy – AI Robotics
 Arkin – Behavior-Based Robotics
 Mataric – Create robot coursework
2007
Kutztown University
37
Conclusions regarding
Intelligent Robotics (IR)
2007
Kutztown University
38
IR is AI-complete
Key AI issues central to IR
 Examples discussed above
 New Elsevier series – Foundations of
Artificial Intelligence

 Temporal reasoning
 Knowledge representation
 Autonomous systems and robots
 Learning and vision
 Spatial reasoning
2007
Kutztown University
39
IR is CS-complete
Behavior-based  OOP
 Interleaved control  OS

 Interrupts
 Job scheduling
Tractability  Algorithm D&S
 Path planning  Search
 Vision
 Many other examples

2007
Kutztown University
40