from cognitive spatial mapping to robot mapping margaret jefferies university of waikato new zealand...
TRANSCRIPT
From Cognitive From Cognitive Spatial Mapping Spatial Mapping
to Robot Mappingto Robot Mapping
Margaret JefferiesMargaret JefferiesUniversity of WaikatoUniversity of Waikato
New ZealandNew ZealandHans-WissenschaftskollegHans-Wissenschaftskolleg
University of BremenUniversity of BremenGermanyGermany
Autonomous Mobile RobotsAutonomous Mobile Robots
Robots might not be taking over the world any time soon but they could soon rule the roost if most New Zealanders have their way.
More than two-thirds of New Zealanders would welcome robots to do chores around the house, according to a study of 750 people, commissioned by Honda. Most people wanted robots to help with housework, many wanted an extra mechanical hand with the washing up and some wanted a robot to mow the lawns.
Politicians and the All Blacks need to watch their backs – some respondents suggested robots should replace politicians and that a team of robots might fare better than the present rugby team.
Some people said they would even swap their partners for robots. Women were keener for a robotic partner, with 5.5 per cent saying they would like to switch, compared with just 3.3 per cent of men wanting to replace their partner.
Autonomous Mobile RobotsAutonomous Mobile RobotsMappingMapping
Robot computes its own map from it own Robot computes its own map from it own
experience of its environment with its experience of its environment with its
imperfect sensors and imperfect odometryimperfect sensors and imperfect odometry
What’s the problem?What’s the problem?
DemoDemo
Simultaneous Localisation and Simultaneous Localisation and Mapping (SLAM)Mapping (SLAM)
Robot needs to estimate its location at the same Robot needs to estimate its location at the same
time it is estimating its maptime it is estimating its map
The localisation problem
ApproachesApproaches
• Absolute Metric Mapping Absolute Metric Mapping
(Global metric mapping)(Global metric mapping)
• Topological MappingTopological Mapping
(Local metric maps)(Local metric maps)
Representation Representation Global MapsGlobal Maps
• Global evidence-grid approach Global evidence-grid approach
Global metric map
Global metric map
The Correspondence Problem (Closing the Cycle)
Topological RepresentationsTopological Representations
Topological RepresentationsTopological Representations
The Correspondence Problem (Closing the Cycle)
From Cognitive Spatial Mapping From Cognitive Spatial Mapping to Robot Mappingto Robot Mapping
Cognitive MapCognitive Map
An agents (human animal or robot’s) An agents (human animal or robot’s) memory of the spatial environmentmemory of the spatial environment
From Cognitive Spatial Mapping From Cognitive Spatial Mapping to Robot Mappingto Robot Mapping
• Draw inspiration from the way in which Draw inspiration from the way in which
humans and animals solve similar problemshumans and animals solve similar problems
• Study the way humans and animals solve Study the way humans and animals solve
similar spatial mapping problems (to robots)similar spatial mapping problems (to robots)
The Local SpaceThe Local Space
• The space that appears to enclose the viewerThe space that appears to enclose the viewer
• Initial notion of “where am I” Initial notion of “where am I”
• A container where objects are located and A container where objects are located and
where actions take placewhere actions take place
Bounded SpaceBounded Space
O’Keefe and Burgess Nature 1996 - hippocampus
Bounded spaceBounded space
• Russell Epstein and Nancy KanwisherRussell Epstein and Nancy Kanwisher– Nature (1998), Neuron (1999)Nature (1998), Neuron (1999)
• Parahippocampus encodes the layout of the Parahippocampus encodes the layout of the local space – the enclosed spacelocal space – the enclosed space
Bounded spaceBounded space
• Environmental Psychologists / GeographersEnvironmental Psychologists / Geographers
• 1980’s work of the Kaplans1980’s work of the Kaplans
• Stamps and Smith (2004)Stamps and Smith (2004)
The Local Space is The Local Space is GeometricGeometric
• Ken Cheng Ken Cheng – Cognition (1986)Cognition (1986)
• Margules and Gallistel Margules and Gallistel – Animal Learning and Behavior(1988)Animal Learning and Behavior(1988)
• Huttenlocher et alHuttenlocher et al– Cognitive Psychology (1979), (1994) Cognitive Psychology (1979), (1994)
• Hermer and Spelke Hermer and Spelke – Nature (1994), Cognition (1996)Nature (1994), Cognition (1996)
Exits are importantExits are important
• Evolutionary psychologistsEvolutionary psychologists– Kaplans (1980s)Kaplans (1980s)– Laslo et al “the Evolution of Cognitive Maps” Laslo et al “the Evolution of Cognitive Maps”
(1993)(1993)
• Environmental psychologistsEnvironmental psychologists– Herzog (2001 – 2004)Herzog (2001 – 2004)– Visual accessVisual access
The Local Mapping ApproachThe Local Mapping Approach
E1 E2
unknown
The Local Mapping ApproachThe Local Mapping Approach
Occlusion Map Local space representation
E1E2
E3
E4
Putting it all togetherPutting it all together
• The Theory of Siegel and White has The Theory of Siegel and White has
dominated thinking in this area since dominated thinking in this area since
it was first proposed in 1975it was first proposed in 1975
landmarkroute / topological survey
global metric
Most computational cognitive mapping approaches use all of these
Putting it all togetherPutting it all together
• The Theory of Siegel and White has The Theory of Siegel and White has
dominated thinking in this area since dominated thinking in this area since
it was first proposed in 1975it was first proposed in 1975
landmarkroute / topological survey
global metric
Most computational cognitive mapping approaches use all of these
E1
E2E3
E4
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E1E2
E3
2
E1E2
E3
2
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E2
E3
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E3
Local space
Topological Map Global Metric Map
DemoDemo
Detecting Cycles in a Global Metric MapDetecting Cycles in a Global Metric Map
• Need to figure out if a newly encountered Need to figure out if a newly encountered
local space is already in the topological local space is already in the topological
map map
• Need to account for the uncertainty in local Need to account for the uncertainty in local
spacespace– In particular occlusionIn particular occlusion
• Want to do it quicklyWant to do it quickly
Closing Cycles in a Topological Closing Cycles in a Topological MapMap
2D Landmarks2D Landmarks
Closing Cycles in a Topological Closing Cycles in a Topological MapMap
2D Landmarks2D Landmarks
• Find (eventually) a signature that identifies Find (eventually) a signature that identifies
the the local space from wherever it is the the local space from wherever it is
approachedapproached
• Learn what it is that makes each local Learn what it is that makes each local
space different from all the othersspace different from all the others
• Whenever we compute a new local space Whenever we compute a new local space
we match it against these signatureswe match it against these signatures
Signature learningSignature learning• A backprop Neural Network
• Feature selection
• Input values are discretised into intervals (200mm) and 45o
• Classification – Output values between 0 and 1 indicate the degree of similarity
12
3
4 5
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71
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4 5
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11
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34
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Matches 2
Local Local
spacespace11 22 33 44 55 66 77 88 99 1010 1111
PredictionPrediction .78.78 .94.94 .89.89 .71.71 -.11-.11 .72.72 .18.18 .51.51 .34.34 .36.36 .04.04
2*1
2
34
5
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9
1011
DisadvantageDisadvantage
• NN doesn’t tell us how the local spaces match just that NN doesn’t tell us how the local spaces match just that
they do.they do.
• Need to find the connectivityNeed to find the connectivity
ASRASR 11 22 33 44 55 66 77 88 99 1010
PredictionPrediction .46.46 .97.97 .91.91 .48.48 .64.64 .26.26 .57.57 .88.88 .15.15 .77.77
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45
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89
10
Best prediction is for 2
Should be 3
3D Visual Landmarks3D Visual Landmarks
ConclusionConclusion
• Recognising places they have been to Recognising places they have been to before is a hard problem for robotsbefore is a hard problem for robots
• There is no perfect solution!There is no perfect solution!
• Then there is the dynamics of the Then there is the dynamics of the environment to contend withenvironment to contend with