1. Part II Chapter 9: Topological Path Planning
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

2. Chapter 9: Topological Path Planning
Objectives
Define the difference between natural and artificial landmarks; give one example of each
Given a description of an indoor office environment and a set of behaviors, build a relational graph representation labeling the distinctive places and local control strategies for gateways
Describe in one or two sentences: gateway, image signature, visual homing, viewframe, orientation region
Given a figure showing landmarks, create a topological map showing landmarks, landmark pair boundaries, and orientation regions
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

3. Chapter 9: Topological Path Planning
Where am I going? Mission planning
What’s the best way there? Path planning
Where have I been? Map making
Where am I? Localization
Navigation
Carto-
grapher
Mission
Planner
deliberative
How am I going to get
there?
Behaviors
reactive
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

4. Chapter 9: Topological Path Planning
Spatial Memory
What’s the Best Way There? depends on the representation of the world
A robot’s world representation and how it is maintained over time is its spatial memory
Attention
Reasoning
Path planning
Information collection
Two forms
Route (or qualitative)
Layout (or metric)
Layout leads to Route, but not the other way
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

5. Route, or Qualitative Navigation
Two categories
Relational
spatial memory is a relational graph, also known as a topological map
use graph theory to plan paths
Associative
spatial memory is a series of remembered viewpoints, where each viewpoint is labeled with a location
good for retracing steps

6. Topological Maps Use Landmarks
A landmark is one or more perceptually distinctive features of interest on an object or locale of interest
Natural landmark: configuration of existing features that wasn’t put in the environment to aid with the robot’s navigation (ex. gas station on the corner)
Artificial landmark: set of features added to the environment to support navigation (ex. highway sign)
Roboticists avoid artificial landmarks!
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

7. Desirable Characteristics of Landmarks
Recognizable (can see it when you need to)
Passive
Perceivable over the entire range of where the robot might need to view it
Distinctive features should be globally unique, or at least locally unique
Perceivable for the task (can extract what you need from it)
ex. can extract relative orientation and depth
ex. unambiguously points the way
Be perceivable from many different viewpoints
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

8. Chapter 9: Topological Path Planning
Example Landmarks
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

9. Gateway is an opportunity to change path heading
floor plan
Gateway is an opportunity
to change path heading
relational graph
Relational Methods
Nodes: landmarks, gateways,
goal locations
Edges: navigable path

10. Problems with early relational graphs
Not coupled with how the robot would get there
Shaft encoder uncertainty accumulates
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

11. Kuipers and Byun: Spatial Hierarchy
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

12. Distinctive Place Approach
Local control strategies (behaviors
to get robot between DPs)
Distinctive Places (recognizable, &
at least locally unique)
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

13. Actually Getting to a Distinctive Place: Neighborhoods
boundary
distinctive
place (within
the corner)
path of robot as it moves
into neighborhood and
to the distinctive place
Use one behavior until sees the DP (exteroceptive
cueing) then swap to a landmark localization behavior

14. Chapter 9: Topological Path Planning
Class Exercise
Create a relational graph for this floorplan
Label each edge with the appropriate LCS: mtd, fh
Label each node with the type of gateway: de, t, r r1 r2
de1
de3
de2 r3 r4 t1 t2 t3 fh
mtd
Room 1
Room 2
Room 3
Room 4
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

15. Chapter 9: Topological Path Planning
Case Study
Representation
Sequencing of behaviors based on current perception (releasers) and subgoal
Algorithm
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

16. Chapter 9: Topological Path Planning
Hd nodes because
Have different perception
R3->R7
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

17. Chapter 9: Topological Path Planning
Transition Table TO
FROM H F R Hd
Navigate-Hall
Undefined
Navigate-Foyer
Navigate-Door
Navigate-door
Navigate-hall
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

18. Path Planning Algorithm
Relational graph, so any single source shortest path algorithm will work (Dijkstra’s)
If wanted to visit all rooms, what algorithm would you use?
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

19. Chapter 9: Topological Path Planning
Execution
Exception subscript
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

20. Chapter 9: Topological Path Planning
Associative Methods
Visual Homing
bees navigate to their hive by a series of image signatures which are locally distinctive (neighborhood)
QualNav
the world can be divided into orientation regions (neighborhoods) based on perceptual events caused by landmark pair boundaries
Assumes perceptual stability, perceptual distinguishability
Randal
Nelson,
URochester
Daryl
Lawton,
Advanced
Decision
Systems
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

21. Chapter 9: Topological Path Planning
Image Signatures
The world
Tesselated (like faceted-eyes)
Resulting signature
for home
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

22. Chapter 9: Topological Path Planning
Move to match the
template
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

23. OR2 OR1 Topological Representation as Orientation Regions Metric Map
tree
building
radio
tower
mountain
OR1
OR2
Metric
Map
Topological
Representation
as Orientation
Regions

24. Chapter 9: Topological Path Planning
Summary
Route, qualitative, and topological navigation all refer to navigating by detecting and responding to landmarks.
Landmarks may be natural or artificial; roboticists prefer natural but may have to use artificial to compensate for robot sensors
There are two type of qualitative navigation: relational and associative
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning

25. Chapter 9: Topological Path Planning
Summary (cont.)
Relational methods use graphs (good for planning) and landmarks
The best known relational method is distinctive places
Distinctive places are often gateways
Local control strategies are behaviors
Associative methods remember places as image signature or a viewframe extracted from a signature
can’t really plan a path, just retrace it
direct stimulus-response coupling by matching signature to current perception
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000
Chapter 9: Topological Path Planning