Path Planning for A Universal Indoor Navigation System · Path Planning for A Universal Indoor...
Transcript of Path Planning for A Universal Indoor Navigation System · Path Planning for A Universal Indoor...
Path Planning for A Universal IndoorNavigation System
E. Kahale, P. C. Hanse, V. DESTIN, G. UZAN, and J.LOPEZ-KRAHE
THIM Laboratory (EA 4004 CHArt)University of Paris8
France
ICCHP’16, 13 – 15, July 2016Linz, Austria
Introduction Modeling Path Calculation Simulation Results Conclusion
Outline
1 Introduction
2 ModelingSurface ModelingUser Profile
3 Path CalculationArduousness CriterionOptimal Path Generation
4 Simulation Results
5 Conclusion
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Introduction
How can I reach mydestination ???
Airports
Commercial Centers
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Introduction
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Problem Statement
ObjectiveIncrease the mobility of persons in public-access building, taking into account allpotential difficulties that users might have in accomplishing different tasks ininteraction with their environment (which can be unfamiliar)
ChallengesIndoor environment
Highly distributive surfacesMulti-levels
Path PlanningInclude all personal difficulties (related to the displacement) in pathcalculationAvoiding obstacles
Proposed Solution and OriginalityUse a topological representation of the space through graph-based approachesIntroduce a new optimization criterion : the arduousnessEmploy a Universal design Concept
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Introduction Modeling Path Calculation Simulation Results Conclusion
Outline
1 Introduction
2 ModelingSurface ModelingUser Profile
3 Path Calculation
4 Simulation Results
5 Conclusion
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Surface Modeling
Building StructureMulti-levelsJunction elements
Each level :Many potential destinationsAmenitiesHighly distributive surfaces
Proposed ModelingTopological Representation :
Valued digraphEach walkable space is consideredas a nodeJunction elements and somespecified amenities are consideredas edges
Each node in the previousdigraph is itself a sub-digraph
Magnetic Building - Beagrenellecommercial center, Paris - France
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Surface Modeling
Building StructureMulti-levelsJunction elements
Each level :Many potential destinationsAmenitiesHighly distributive surfaces
Proposed ModelingTopological Representation :
Valued digraphEach walkable space is consideredas a nodeJunction elements and somespecified amenities are consideredas edges
Each node in the previousdigraph is itself a sub-digraph
Magnetic Building - Beagrenellecommercial center, Paris - France
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Surface ModelingSub-digraph generation
Needs
Taking into account the presence of obstacles within walkable surfaces
Proposed Solution
Apply approaches conventionally used in mobile robotics fieldsX Visibility-based method :
⇒ Two nodes share an edge if they are within line of sight ofeach other, i.e.
eij 6= ∅⇐⇒ svi + (1− s)vj ∈ Qfree ∀s ∈ [0, 1]
where Qfree denotes the walkable surfaces⇒ All points in the free space are within line of sight of at least
one node on the visibility map
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Surface ModelingSub-digraph generation
Visibility Graph Construction∗
Algorithm 1 Rotational Plane Sweep AlgorithmInput: A set of vertices Vi and a vertex vOutput: A subset of vertices from Vi that are within line
of sight of v1: For each vertex vi , calculate αi , the angle from the
horizontal axis to the line segment vvi2: Create the vertex list ε, containing the αi ’s stored in
increasing order3: Create the active list S, containing the sorted list of
edges that intersect the horizontal half-line emanatingfrom v
4: for all αi do5: if Vi is visible to v then6: Add the edge (v, vi ) to thr visibility graph7: end if8: if vi is the beginning of an edge, E , not in S then9: Insert the E into S
10: end if11: if vi is the end of an edge in S then12: Delete the edge from S13: end if14: end for
Polygonal configuration space with a start and goaland visibility connections with respect to vstart
Visibility map∗H. Choset et al., Principles of Robot Motion-Theory, Algorithms, and Implementation, The MIT Press,
Cambridge, England, 2005
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User Profile
In French LawPeople with disabilities are classified in the following categories:
1 Physical2 Sensory3 Mental
4 Psychic5 Cognitive6 Multiple Impairment
In this workDisability = a set of difficulties to complete a task in interaction with agiven environment
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User Profile
Pedestrian movement asks the user to:
Interact with his physical and social environmentMemorize placesEstablish connections between networksUse facilities
12 potential classes characterizing users and having an impact on thecomputation of an optimal path have been determined
Related to the use of hands◦ Trembling or involuntary movements◦ Difficult use of hands
Related to the displacement
◦ Supporting stick, crutches, walker◦ Stiffness, joint or muscle pains◦ Shortness of breath, respiratory or heart problems◦ Electric wheelchair◦ Manual wheelchair
Related to the vision
◦ Blindness (use of a walking cane)◦ Glare, fog, blur, opacity, paleness◦ Fragmented, Tunnel or peripheral vision◦ Blindness (use of guide dog)◦ Difficulty reading
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Introduction Modeling Path Calculation Simulation Results Conclusion
Outline
1 Introduction
2 Modeling
3 Path CalculationArduousness CriterionOptimal Path Generation
4 Simulation Results
5 Conclusion
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Arduousness Criterion
NeedsProvided path must:
Satisfy the physical capacities of the userMinimize the effort needed to accomplish each step
PropositionIntroduce a new coefficient describing the arduousness associatedto each edge in the digraph
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Arduousness Criterion
NeedsProvided path must:
Satisfy the physical capacities of the userMinimize the effort needed to accomplish each step
PropositionIntroduce a new coefficient describing the arduousness associatedto each edge in the digraph
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Arduousness Criterion
Determine the inherent characteristics for each amenityidentified as an edgeExample:
Inherent characteristic for a stairStaircase openwork (without riser)
With two flightsWith three flights
SpiralWithout right handrail, unusable left handWithout left handrail, unusable right hand
Without handrailShortLong
Down stairUp stair
Without orientation (Bi-directional)Presence of palisade narrowing the width of the stairPresence of scaffold narrowing the width of the stair
Presence of barrier blocking access
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Arduousness Criterion
For each property we define a weighting coefficient γu,ei So theglobal weight for the edge ei is given by:
Γei =∏
γu,ei
where γu,ei ∈ [0, 1] ⇒ Γei ∈ [0, 1], and
Γei =
{0; Impassable1; No constraint
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Arduousness CriterionExample
StairInherent characteristic Weight User’s Difficulties Weight
Staircase openwork (without riser) 0,9 Rolling bulky object 0,8With two flights 0,9 Carrying bulky object 0,8With three flights 0,8 Trembling or involuntary movements (upper
limbs)0,8
Spiral 0,8 Difficult use of hands 0,7Without right handrail, unusable left hand 0,9 Blindness (use of a walking cane) 0,9Without left handrail, unusable right hand 0,9 Glare, fog, blur, opacity, paleness 0,9Without handrail 0,9 Stiffness, joint or muscle pains (lower limbs) 0,7Short 1 Fragmented, Tunnel or peripheral vision 0,9Long 0,9 Difficulty reading 1Down stair 1 Blindness (use of guide dog) 1Up stair 0,9 Supporting stick, crutches, walker 0,6Without orientation (Bi-directional) 0,9 Shortness of breath, respiratory or heart problems 0,8Presence of palisade narrowing the width of the stair 0,95 Electric wheelchair 0Presence of scaffold narrowing the width of the stair 0,95 Manual wheelchair 0Presence of barrier blocking access 0
The arduousness coefficient of a stair WITHOUT HANDRAIL, SHORT et GOING DOWN for a person havingHEART PROBLEMS and CARRYING BULKY OBJECT is given by:
Γei = 0.9× 1× 1× 0.8× 0.8 = 0.9× 0.64 = 0.576
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Optimal Path Generation
NeedsProvided path must:X Satisfy the physical capacities of the user
Minimize the effort needed to accomplish each step
Problem StatementCombinatorial Optimization Problem / Operational ResearchShortest Path Problem
Proposed SolutionUse a path planning method conventionally applied in mobilerobots navigation systems
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Optimal Path Generation
Dijkstra’s Algorithm† ‡ § ¶
X Find the shortest pathX Ensure the optimality of the solution
X Replace the distance by 1/Γei ⇒ Maximize Γei ⇔ Providespath with the minimum arduousness cost
†H. Choset et al. Principles of Robot Motion-Theory, Algorithms, andImplementation, The MIT Press, Cambridge, England, 2005‡S.M. LaValle, Planning Algorithms, Cambridge University Press, U.K.:
Cambridge, 2006§B. Siciliano et al. Robotics: Modelling, Planning and Control, Springer Verlag,
London, 2009¶D. Jungnickel, Graphs, Networks and Algorithms. Fourth Edition, Springer
Verlag, London, 2013E. KAHALE et al. - ICCHP’16 16/21
Introduction Modeling Path Calculation Simulation Results Conclusion
Optimal Path Generation
Dijkstra’s Algorithm† ‡ § ¶
X Find the shortest pathX Ensure the optimality of the solution
X Replace the distance by 1/Γei ⇒ Maximize Γei ⇔ Providespath with the minimum arduousness cost
†H. Choset et al. Principles of Robot Motion-Theory, Algorithms, andImplementation, The MIT Press, Cambridge, England, 2005‡S.M. LaValle, Planning Algorithms, Cambridge University Press, U.K.:
Cambridge, 2006§B. Siciliano et al. Robotics: Modelling, Planning and Control, Springer Verlag,
London, 2009¶D. Jungnickel, Graphs, Networks and Algorithms. Fourth Edition, Springer
Verlag, London, 2013E. KAHALE et al. - ICCHP’16 16/21
Introduction Modeling Path Calculation Simulation Results Conclusion
Outline
1 Introduction
2 Modeling
3 Path Calculation
4 Simulation Results
5 Conclusion
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Simulation Results
Proof of concept application has been :developed in JAVAintegrated in a Samsung Galaxy S6 (64-bit processor)
Increase the robustness facing map data collection errorsData format or unit errorsImprecision in the location of points of interest (outsidewalkable surfaces)
Two scenarios were chosen
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Simulation ResultsScenario 1
Scenario 1 : Person without difficulties
(a) Departing point → Escalator (b) Escalator → Arrival point
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Simulation ResultsScenario 2
Scenario 2 : Wheelchair user
(a) Departing point → Lift (b) Lift → Arrival point
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Outline
1 Introduction
2 Modeling
3 Path Calculation
4 Simulation Results
5 Conclusion
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Conclusion and Future Works
Novel path planning strategy for indoor navigation system based on a universaldesign concept
Surface ModelingTopological representation (digraph)Highly distributive surfaces (family of paths, obstacle avoidance)Determine the inherent characteristics of each amenity identified as anedge
User Profile
Identify 12 potential difficulties having an impact on the displacement
Optimal path generationIntroduce new criterion : Arduousness for optimizationMinimizing Arduousness : Dijkstra’s Algorithm
Validating through Simulation
Experimentation in a large Parisian railway (in discussion)
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Thank You!
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