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

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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

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

9Part II

Chapter 9:Topological Path Planning

Page 2: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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?

Page 3: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 4: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 5: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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!

Page 6: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 7: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 7

9 Example Landmarks

Page 8: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 9: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 10: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 10

9 Kuipers and Byun: Spatial Hierarchy

Page 11: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 12: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 13: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 14: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 15: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 16: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 17: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 18: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 20: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 24: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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

Page 25: 9 Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning1 Part II Chapter 9: Topological Path Planning

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