4
The Reactive Paradigm
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary
• Describe the Reactive Paradigm in terms of the 3 robot primitives and its organization of sensing
• List the characteristics of a reactive robotic system, and discuss the connotations of surrounding the reactive paradigm
• Describe the two dominant methods for combining behaviors in a reactive architecture: subsumption and potential field summation
• Be able to program a behavior using pfields
• Be able to construct a new potential field from primitive pfields and sum pfields to generate an emergent behavior
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 1

4 Review:
Lessons from Biology
• Programs should decompose complex actions into behaviors. Complexity emerges from concurrent behaviors acting independently
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary
• Agents should rely on straightforward activation mechanisms such as IRM
• Perception filters sensing and considers only what is relevant to the task (action-oriented perception)
• Behaviors are independent but the output may be used in many ways including: combined with others to produce a resultant output or to inhibit others
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 2

4
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary
Hierarchical Organization is
“Horizontal”
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 3

4
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary
More Biological is “Vertical”
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 4

4 Sensing is
Behavior-Specific or Local
Review
Organization
-SA
beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary
Behaviors can “share” perception without knowing it
This is behavioral sensor fusion
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 5

4
Reactive Robots
RELEASER behavior
SENSE ACT
Overview
History
Reactive
USAR
Summary
• Most apps are programmed with this paradigm
• Biologically based:
– Behaviors (independent processes), released by perceptual or internal events (state)
– No world models or long term memory
– Highly modular, generic
– Overall behavior emerges
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 6

4
Overview
History
Reactive
USAR
Summary
Example 1: Robomow
• Behaviors?
• Random
• Avoid
– Avoid(bump=obstacle)
– Avoid(wire=boundary)
• Stop
– Stop(tilt=ON)
• All active www.friendlymachines.com
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 7

4
Overview
History
Reactive
USAR
Summary
Example 2: My Real Baby
• Behaviors?
• Touch-> Awake
• Upside down & Awake-> Cry
• Awake & Hungry -> Cry
• Awake & Lonely -> Cry www.irobot.com
•
Note can get crying from multiple behaviors
• Note internal state (countdown timer on Lonely)
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 8

4
Reactive
• Historically, there are two main styles of creating a reactive system
– Subsumption architecture
• Layers of behavioral competence
• How to control relationships
– Potential fields
• Concurrent behaviors
• How to navigate
• They are equivalent in power
• In practice, see a mixture of both layers and concurrency
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 9

4
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary
Subsumption:
Rodney Brooks
From http://www.spe.sony.com/classics/fastcheap/index.html
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 10

4
Subsumption Philosophy
•
Modules should be grouped into layers of competence
Review
Organization
-SA
-beh. specific
Subsumption
Philosophy
-Level 0
-Level 1
-Level 2
Summary
• Modules in a higher lever can override or subsume behaviors in the next lower level
– Suppression: substitute input going to a module
– Inhibit: turn off output from a module
• No internal state in the sense of a local, persistent representation similar to a world model.
•
Architecture should be taskable : accomplished by a higher level turning on/off lower layers
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 11

4
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
Level 0
-Level 1
-Level 2
Summary
Level 0: Runaway
PS
RUN AWAY
MS follow-corridor 2 wander 1 runaway 0
PS MS
HALT
COLLIDE
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 12

4
Example Perception: Polar Plot
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary • Plot is ego-centric if sensing is ego-centric, can often eliminate need for memory, representation
• Plot is distributed (available to whatever wants to use it)
• Although it is a representation in the sense of being a data structure, there is no memory (contains latest information) and no reasoning (2-3 means a “wall”)
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 13

4
Level 1: Wander
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary
PS
WANDER
MS encoders
PS
AVOID
MS
Note sharing of
Perception, fusion follow-corridor 2 wander 1 runaway 0
What would
Inhibition do?
14 Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm

4
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary
LIGHT
Class Exercise
PHOTO-
TROPHISM move2light 2 wander 1 runaway 0
S
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 15

4
Level 2: Follow-Corridors
STAY-IN-MIDDLE
PS MS
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary follow-corridor 2 wander 1 runaway 0
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 16

4
Class Exercise
• Design the roomba with subsumption
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 17

4
Subsumption Review
• What is the Reactive Paradigm in terms of primitives?
• What is the Reactive Paradigm in terms of sensing?
Review
Organization
-SA
-beh. specific
Subsumption
-Philosophy
-Level 0
-Level 1
-Level 2
Summary
• Does the Reactive Paradigm solve the Open World problem?
• How does the Reactive Paradigm eliminate the problem?
• What is the difference between a behavior and a level of competence?
frame
• What is the difference between suppression and inhibition in subsumption?
18 Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm

4 Potential Fields:
Ron Arkin
From http://www.cc.gatech.edu/aimosaic/faculty/arkin
Introduction to AI Robotics (MIT Press)
From http://www.cc.gatech.edu/aimosaic/robot-lab/MRLhome.html
Chapter 4: The Reactive Paradigm 19

4
Potential Fields Philosophy
• The motor schema component of a behavior can be expressed with a potential fields methodology
– A potential field can be a “primitive” or constructed from primitives which are summed together
– The output of behaviors are combined using vector summation
• From each behavior, the robot “feels” a vector or force
– Magnitude = force, strength of stimulus, or velocity
– Direction
• But we visualize the “force” as a field, where every point in space represents the vector that it would feel if it were at that point
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 20

4
Example: Run Away via Repulsion
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 21

4
5 Primitive Potential Fields
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 22

4 Draw These Now!
Common fields in behaviors
• Uniform
– Move in a particular direction, corridor following
• Repulsion
– Runaway (obstacle avoidance)
• Attraction
– Move to goal
• Perpendicular
– Corridor following
• Tangential
– Move through door, docking (in combination with other fields)
• random
– do you think this is a potential field? what would it look like?
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 23

4
Class Exercise
• Name the field you’d use for
– Moving towards a light
– Avoiding obstacles
Attractive
Repulsive
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 24

4 Combining Fields for
Emergent Behavior obstacle obstacle
If robot were dropped anywhere on this grid, it would want to move to goal and avoid obstacle:
Behavior 1: MOVE2GOAL
Behavior 2: RUNAWAY
The output of each independent behavior is a vector, the 2 vectors is summed to produce emergent behavior
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 25

4
Fields and Their Combination
2 meters
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 26

4
Robot only feels vectors for this point when it (if) reaches that point
Path Taken
• If robot started at this location, it would take the following path
• It would only “feel”the vector for the location, then move accordingly, “feel” the next vector, move, etc.
• Pfield visualization allows us to see the vectors at all points, but robot never computes the “field of vectors” just the local vector
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 27

4
Discussion
• Could you represent the Arctic Tern feeding behavior with potential fields?
– what happens with multiple red dots?
– can you inhibit with potential fields?
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 28

4 Example: follow-corridor or follow-sidewalk
Note use of
Magnitude profiles:
Perpendicular decreases
Perpendicular Uniform
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm
Combined
29

4 Class Exercise:
Draw Fields for Wall-Following
(assume that robot stands still if no wall)
Just half of a follow-corridor, but…
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 30

4 But how does the robot see a wall without reasoning or intermediate representations?
• Perceptual schema “connects the dots”, returns relative orientation
PS:
Sonars
Find-wall
Introduction to AI Robotics (MIT Press) orientation MS: Perp.
MS: Uniform
Chapter 4: The Reactive Paradigm
S
31

4
OK, But why isn’t that a representation of a wall?
• It’s not really reasoning that it’s a wall, rather it is reacting to the stimulus which happens to be smoothed
(common in neighboring neurons)
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 32

4
Level 0: Runaway
Note: multiple instances of a behavior vs. 1:
Could just have 1
Instance of RUN AWAY,
Which picks nearest reading;
Doesn’t matter, but this
Allows addition of another
Sonar without changing the
RUN AWAY behavior
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 33

4
Level 1: Wander
Wander is
Uniform, but
Changes direction aperiodically
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 34

4
Level 2: Follow Corridor
Follow-corridor
Should we
Leave
Run Away
In? Do we
Need it?
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 35

4
Pfields
• Advantages
– Easy to visualize
– Easy to build up software libraries
– Fields can be parameterized
– Combination mechanism is fixed, tweaked with gains
• Disadvantages
– Local minima problem (sum to magnitude=0)
• Box canyon problem
– Jerky motion
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 36

4
Example: Docking Behavior
Orientation, ratio of pixel counts
 tangent vector
Total count
 attraction vector
Introduction to AI Robotics (MIT Press)
• Arkin and Murphy, 1990, Questa,
Grossmann, Sandini, 1995, Tse and
Luo, 1998, Vandorpe, Xu, Van
Brussel, 1995. Roth, Schilling, 1998,
37

4
Docking Behavior Video
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 38

4 Class Discussion:
When Does a Field End?
• Imagine the case of a “SodaPup” robot (MIT)
– task: find and pick up a Coca-Cola can
– environment: red cans are only red object in world
– behavior: ??
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 39

4
Pfields Summary
• Reactive Paradigm: SA, sensing is local
– Solves the
Open World problem by emulating biology
– Eliminates the frame problem by not using any global or persistent representation
– Perception is direct, ego-centric, and distributed
• Two architectural styles are: subsumption and pfields
• Behaviors in pfield methodologies are a tight coupling of sensing to acting; modules are mapped to schemas conceptually
• Potential fields and subsumption are logically equivalent but different implementations
• Pfield problems include
– local minima (ways around this)
– jerky motion
– bit of an art
Introduction to AI Robotics (MIT Press) Chapter 4: The Reactive Paradigm 40