9 introduction to ai robotics (mit press), copyright robin murphy 2000 chapter 9: topological path...

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

9Part 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?

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

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

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!

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

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

9 Example Landmarks

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

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

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

9 Kuipers and Byun: Spatial Hierarchy

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

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

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

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

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

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

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

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

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

9

Move to match thetemplate

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

9

tree

building

radiotower

mountain

OR1OR2

MetricMap

TopologicalRepresentationas OrientationRegions

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

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

Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 23

9

R3->R7

Hd nodes becauseHave different perception

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

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

Introduction to AI Robotics (MIT Press), copyright Robin Murphy 2000 Chapter 9: Topological Path Planning 26

9 Execution

Exception subscript

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)

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

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

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