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Transcript of 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path...
![Page 1: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning.](https://reader031.fdocuments.net/reader031/viewer/2022013004/56649e8a5503460f94b8ee9f/html5/thumbnails/1.jpg)
Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 1
9Part II
Chapter 9:Topological Path Planning
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 2
9 Navigation• Where am I going? Mission
planning
• What’s the best way there? Path planning
• Where have I been? Map making
• Where am I? Localization
MissionPlanner
Carto-grapher
BehaviorsBehaviorsBehaviorsBehaviors
deli
bera
tive
reac
tiveHow am I going to get
there?
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 3
9 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
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning
9 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
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 5
9 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!
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 6
9 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
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 7
9 Example Landmarks
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning
9 floor plan
relational graph
Relational Methods
Nodes: landmarks, gateways,goal locations
Edges: navigable path
Gateway is an opportunityto change path heading
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 9
9 Problems with early relational graphs
• Not coupled with how the robot would get there
• Shaft encoder uncertainty accumulates
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 10
9 Kuipers and Byun: Spatial Hierarchy
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 11
9
Distinctive Places (recognizable, &at least locally unique)
Local control strategies (behaviorsto get robot between DPs)
Distinctive Place Approach
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 12
9 Hill climbing algorithm
• Directs the robot around in the neighborhood until a measurement function indicates that the robot is at a position where the feature values are maximized
• the point where it happens is the distinctive place,
• the algorithm always chooses the next step which is the highest (without looking ahead)
• the robot always moves in the direction which causes increase in the measurement function
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning
9neighborhoodboundary
distinctiveplace (withinthe corner)
path of robot as it moves into neighborhood and
to the distinctive place
Actually Getting to a Distinctive Place: Neighborhoods
Uses one behavior until sees the DP (exteroceptivecueing) then swaps to a landmark localization behavior
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 14
9 Advantages and disadvantages
• Distinctive place concept eliminates any navigational errors at each node
• supports discovery of new landmarks as the robot explores an unknown environment
• distinctive places may be hard to find
• problems with perception
• learning local control strategy is hard
• problems with indistinguishable locations
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 15
9 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
Room 1 Room 2
Room 3 Room 4
r1 r2
de1
de3
de2r3 r4
t1 t2 t3fh fh fh
fh
fh
mtd
mtd
mtd
mtd
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 16
9 Associative Methods
• Create a behavior which converts sensor observations into the direction to go to reach a particular landmark
• that landmark has to have two attributes - 1. Perceptual stability - close views of a landmark are similar 2. Perceptual distinguishibility - far away views are different
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 17
9 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
RandalNelson,URochester
DarylLawton,AdvancedDecision Systems
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 18
9 Image Signatures
The world Tesselated (like faceted-eyes)
Resulting signaturefor home
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 19
9
Move to match thetemplate
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning
9
tree
building
radiotower
mountain
OR1OR2
MetricMap
TopologicalRepresentationas OrientationRegions
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 21
9 Associative Methods
• Vehicle can directly perceive when it has entered a new orientation region, by sensing the transition through landmark- pair boundary
• a set of angles recorded at a point along the path is called a viewframe
• advantages - tight coupling of sensing to homing, - image signature and viewframe do not require explicit recognition of a landmark
• disadvantages - require massive storage, - are brittle in the presence of a dynamic world
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 22
9 Case Study
• Representation - topological map as an ASCII file in Backus-Naur form, the world is orthogonal
• three node types - room, hall and foyer
• the map does not show if a corridor is blocked
• outside of each door is marked
• cartographer construct the route using Dijkstra shortest path algorithm
• task manager uses the route to select appropriate abstract navigation behavior (ANB)
• Sequencing of behaviors based on current perception (releasers) and subgoal
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 23
9
R3->R7
Hd nodes becauseHave different perception
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 24
9 Transition Table
TO
FROM H F R Hd
H Navigate-Hall
Navigate-Hall
Undefined Navigate-Hall
F Navigate-Hall
Navigate-Foyer
Navigate-Door
Navigate-Door
R Undefined Navigate-door
Navigate-door
Navigate-door
Hd Navigate-hall
Navigate-hall
Navigate-door
Navigate-hall
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 25
9 Task manager
• Not all combinations of nodes are permitted
• table not necessarily symmetric
• ANB uses information from the database entries corresponding to nodes as parameters for instantiating the script to the current waypoint pair,
• in case of a blocked path TM terminates the currently active ANB, directs the robot to the last known node and request from the cartographer a new path from this node to the destination
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 26
9 Execution
Exception subscript
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 27
9 Navigation Scripts
• Switch(door) case door-not-found: //initialization phase //follow wall until find door if wall is found wallfollow to door else move-ahead to find a wall case door-found: //nominal activity phase move-through-door(door-location)
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 28
9 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
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 29
9 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
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Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 30
9 What you should be able to do
• 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