Path Planning for A Universal Indoor Navigation System

Transcription

1 Path Planning for A Universal Indoor Navigation 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 2016 Linz, Austria

2 Outline 1 Introduction 2 Modeling Surface Modeling User Profile 3 Path Calculation Arduousness Criterion Optimal Path Generation 4 Simulation Results 5 Conclusion E. KAHALE et al. - ICCHP 16 2/21

3 Introduction Modeling Path Calculation Simulation Results Conclusion Introduction How can I reach my destination??? Commercial Centers Airports Railway stations E. KAHALE et al. - ICCHP 16 3/21

4 Introduction E. KAHALE et al. - ICCHP 16 4/21

5 Problem Statement Objective Increase the mobility of persons in public-access building, taking into account all potential difficulties that users might have in accomplishing different tasks in interaction with their environment (which can be unfamiliar) Challenges Indoor environment Highly distributive surfaces Multi-levels Path Planning Include all personal difficulties (related to the displacement) in path calculation Avoiding obstacles Proposed Solution and Originality Use a topological representation of the space through graph-based approaches Introduce a new optimization criterion : the arduousness Employ a Universal design Concept E. KAHALE et al. - ICCHP 16 5/21

6 Outline 1 Introduction 2 Modeling Surface Modeling User Profile 3 Path Calculation 4 Simulation Results 5 Conclusion E. KAHALE et al. - ICCHP 16 5/21

7 Surface Modeling Building Structure Multi-levels Junction elements Each level : Many potential destinations Amenities Highly distributive surfaces Magnetic Building - Beagrenelle commercial center, Paris - France E. KAHALE et al. - ICCHP 16 6/21

8 Surface Modeling Building Structure Multi-levels Junction elements Each level : Many potential destinations Amenities Highly distributive surfaces Magnetic Building - Beagrenelle commercial center, Paris - France Proposed Modeling Topological Representation : Valued digraph Each walkable space is considered as a node Junction elements and some specified amenities are considered as edges Each node in the previous digraph is itself a sub-digraph E. KAHALE et al. - ICCHP 16 6/21

9 Surface Modeling Sub-digraph generation Needs Taking into account the presence of obstacles within walkable surfaces Proposed Solution Apply approaches conventionally used in mobile robotics fields Visibility-based method : Two nodes share an edge if they are within line of sight of each other, i.e. e ij sv i + (1 s)v j Q free s [0, 1] where Q free denotes the walkable surfaces All points in the free space are within line of sight of at least one node on the visibility map E. KAHALE et al. - ICCHP 16 7/21

10 Surface Modeling Sub-digraph generation Visibility Graph Construction Algorithm 1 Rotational Plane Sweep Algorithm Input: A set of vertices V i and a vertex v Output: A subset of vertices from V i that are within line of sight of v 1: For each vertex v i, calculate α i, the angle from the horizontal axis to the line segment vv i 2: Create the vertex list ɛ, containing the α i s stored in increasing order 3: Create the active list S, containing the sorted list of edges that intersect the horizontal half-line emanating from v 4: for all α i do 5: if V i is visible to v then 6: Add the edge (v, v i ) to thr visibility graph 7: end if 8: if v i is the beginning of an edge, E, not in S then 9: Insert the E into S 10: end if 11: if v i is the end of an edge in S then 12: Delete the edge from S 13: end if 14: end for Polygonal configuration space with a start and goal and visibility connections with respect to v start Visibility map H. Choset et al., Principles of Robot Motion-Theory, Algorithms, and Implementation, The MIT Press, Cambridge, England, 2005 E. KAHALE et al. - ICCHP 16 8/21

11 User Profile In French Law People with disabilities are classified in the following categories: 1 Physical 2 Sensory 3 Mental 4 Psychic 5 Cognitive 6 Multiple Impairment In this work Disability = a set of difficulties to complete a task in interaction with a given environment E. KAHALE et al. - ICCHP 16 9/21

12 User Profile Pedestrian movement asks the user to: Interact with his physical and social environment Memorize places Establish connections between networks Use facilities 12 potential classes characterizing users and having an impact on the computation of an optimal path have been determined Related to the use of hands Related to the displacement Related to the vision Trembling or involuntary movements Difficult use of hands Supporting stick, crutches, walker Stiffness, joint or muscle pains Shortness of breath, respiratory or heart problems Electric wheelchair Manual wheelchair Blindness (use of a walking cane) Glare, fog, blur, opacity, paleness Fragmented, Tunnel or peripheral vision Blindness (use of guide dog) Difficulty reading E. KAHALE et al. - ICCHP 16 10/21

13 Outline 1 Introduction 2 Modeling 3 Path Calculation Arduousness Criterion Optimal Path Generation 4 Simulation Results 5 Conclusion E. KAHALE et al. - ICCHP 16 10/21

14 Arduousness Criterion Needs Provided path must: Satisfy the physical capacities of the user Minimize the effort needed to accomplish each step E. KAHALE et al. - ICCHP 16 11/21

15 Arduousness Criterion Needs Provided path must: Satisfy the physical capacities of the user Minimize the effort needed to accomplish each step Proposition Introduce a new coefficient describing the arduousness associated to each edge in the digraph E. KAHALE et al. - ICCHP 16 11/21

16 Arduousness Criterion Determine the inherent characteristics for each amenity identified as an edge Example: Inherent characteristic for a stair Staircase openwork (without riser) With two flights With three flights Spiral Without right handrail, unusable left hand Without left handrail, unusable right hand Without handrail Short Long Down stair Up stair Without orientation (Bi-directional) Presence of palisade narrowing the width of the stair Presence of scaffold narrowing the width of the stair Presence of barrier blocking access E. KAHALE et al. - ICCHP 16 12/21

17 Arduousness Criterion For each property we define a weighting coefficient γ u,ei global weight for the edge e i is given by: So the Γ ei = γ u,ei where γ u,ei [0, 1] Γ ei [0, 1], and { 0; Impassable Γ ei = 1; No constraint E. KAHALE et al. - ICCHP 16 13/21

18 Arduousness Criterion Example Stair Inherent characteristic Weight User s Difficulties Weight Staircase openwork (without riser) 0,9 Rolling bulky object 0,8 With two flights 0,9 Carrying bulky object 0,8 With three flights 0,8 Trembling or involuntary movements (upper 0,8 limbs) Spiral 0,8 Difficult use of hands 0,7 Without right handrail, unusable left hand 0,9 Blindness (use of a walking cane) 0,9 Without left handrail, unusable right hand 0,9 Glare, fog, blur, opacity, paleness 0,9 Without handrail 0,9 Stiffness, joint or muscle pains (lower limbs) 0,7 Short 1 Fragmented, Tunnel or peripheral vision 0,9 Long 0,9 Difficulty reading 1 Down stair 1 Blindness (use of guide dog) 1 Up stair 0,9 Supporting stick, crutches, walker 0,6 Without orientation (Bi-directional) 0,9 Shortness of breath, respiratory or heart problems 0,8 Presence of palisade narrowing the width of the stair 0,95 Electric wheelchair 0 Presence of scaffold narrowing the width of the stair 0,95 Manual wheelchair 0 Presence of barrier blocking access 0 The arduousness coefficient of a stair WITHOUT HANDRAIL, SHORT et GOING DOWN for a person having HEART PROBLEMS and CARRYING BULKY OBJECT is given by: Γ ei = = = E. KAHALE et al. - ICCHP 16 14/21

19 Optimal Path Generation Needs Provided path must: Satisfy the physical capacities of the user Minimize the effort needed to accomplish each step Problem Statement Combinatorial Optimization Problem / Operational Research Shortest Path Problem Proposed Solution Use a path planning method conventionally applied in mobile robots navigation systems E. KAHALE et al. - ICCHP 16 15/21

20 Optimal Path Generation Dijkstra s Algorithm Find the shortest path Ensure the optimality of the solution H. Choset et al. Principles of Robot Motion-Theory, Algorithms, and Implementation, 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, 2013 E. KAHALE et al. - ICCHP 16 16/21

21 Optimal Path Generation Dijkstra s Algorithm Find the shortest path Ensure the optimality of the solution Replace the distance by 1/Γ ei Maximize Γ ei Provides path with the minimum arduousness cost H. Choset et al. Principles of Robot Motion-Theory, Algorithms, and Implementation, 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, 2013 E. KAHALE et al. - ICCHP 16 16/21

22 Outline 1 Introduction 2 Modeling 3 Path Calculation 4 Simulation Results 5 Conclusion E. KAHALE et al. - ICCHP 16 16/21

23 Simulation Results Proof of concept application has been : developed in JAVA integrated in a Samsung Galaxy S6 (64-bit processor) Increase the robustness facing map data collection errors Data format or unit errors Imprecision in the location of points of interest (outside walkable surfaces) Two scenarios were chosen E. KAHALE et al. - ICCHP 16 17/21

24 Simulation Results Scenario 1 Scenario 1 : Person without difficulties (a) Departing point Escalator (b) Escalator Arrival point E. KAHALE et al. - ICCHP 16 18/21

25 Simulation Results Scenario 2 Scenario 2 : Wheelchair user (a) Departing point Lift (b) Lift Arrival point E. KAHALE et al. - ICCHP 16 19/21

26 Outline 1 Introduction 2 Modeling 3 Path Calculation 4 Simulation Results 5 Conclusion E. KAHALE et al. - ICCHP 16 19/21

27 Conclusion and Future Works Novel path planning strategy for indoor navigation system based on a universal design concept Surface Modeling Topological representation (digraph) Highly distributive surfaces (family of paths, obstacle avoidance) Determine the inherent characteristics of each amenity identified as an edge User Profile Identify 12 potential difficulties having an impact on the displacement Optimal path generation Introduce new criterion : Arduousness for optimization Minimizing Arduousness : Dijkstra s Algorithm Validating through Simulation Experimentation in a large Parisian railway (in discussion) E. KAHALE et al. - ICCHP 16 20/21

28 Thank You! E. KAHALE et al. - ICCHP 16 21/21