Real-Time Multi-Agent Path Planning on Arbitrary Surfaces
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Transcript of Real-Time Multi-Agent Path Planning on Arbitrary Surfaces
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Real-Time Multi-Agent Path Planning on Arbitrary Surfaces
Rafael P. Torchelsen1, Luiz F. Scheidegger1, Guilherme N. Oliveira1, Rui Bastos2, João L. D. Comba1
1Instituto de Informática - PPGC, UFRGS - Brazil
2NVIDIA Corporation
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Obstacle
Real-Time Multi-Agent Path Planning on Arbitrary Surfaces
GoalAgentObstacle
Shortest free path
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Related WorkPlanar Surfaces
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1) Avneesh Sud, Erik Andersen, Sean Curtis, Ming Lin, and Dinesh Manocha. Real-time Path Planning in Dynamic Virtual Environments Using Multi-agent Navigation Graphs. IEEE TVCG 2008
2) S. J. Guy, J. Chhugani, C. Kim, N. Satish, M. Lin, D. Manocha, and P. Dubey. ClearPath: Highly Parallel Collision Avoidance for Multi-Agent Simulation. ACM SIGGRAPH/Eurographics Symposium on Computer Animation 2009
3) Avneesh Sud, Russell Gayle, Erik Andersen, Stephen Guy, Ming Lin, and Dinesh Manocha Real-time Navigation of Independent Agents Using Adaptive Roadmaps. ACM Symposium on Virtual Reality Software and Technology 2007
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Related WorkAgain: Planar Surfaces
Command and Conquer™
Distance computation is cheapEuclidian Distance: The mesh isn't considered on the distance computation
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Contributions
• Multi-agent navigation on non-planar surfaces• Multi-resolution distance computation• GPU-based approach for collision avoidance• CPU/GPU path planning pipeline
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Outline
• Related Work• Background• Global Navigation
– Hierarchical Computation of Distances
• Local Navigation– Collision Grid– Finding an Unobstructed Direction
• Results• Discussion• Conclusion
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Background
• Global Navigation• Local Navigation
Obstacle
GoalAgentObstacle
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Global Navigation
Several fields are need per frame
Constant FPSIncremental Computation
Fast Initial MovementIncremental Resolution
PerformanceParallel Computation
Rafael P. Torchelsen, Francisco Pinto, Rui Bastos and João L. D. Comba. Approximate on-Surface Distance Computation using Quasi-Developable Charts. Computer Graphics Forum v. 28 (Pacific Graphics 2009)
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Hierarchical Computation of Distances
RenderingDistance FieldComputationDistance Field
ComputationDistance FieldComputation
N Threads
f4
r3
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r1A1 AmM Agents A2 A3 A4 ...
Path PlanningPath Planning
Path Planning
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M Threads
CPU GPU
Available
f4
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r1
f4
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Distance Fields Destination Resolution
To be Processed
Fd
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Not Ready
fd
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Ready fd
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Collision Grid
Distance Fields Destination Resolution
Distance Field Slot
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Outline
• Related Work• Background• Global Navigation
– Hierarchical Computation of Distances
• Local Navigation– Collision Grid– Finding an Unobstructed Direction
• Results• Discussion• Conclusion
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Collision Grid
A1 AmM Agents A2 A3 A4
...
Collision GridAdvantage• 1 Agent <-> 1 Cell• Minimal Concurrent Access
• Static Data Structure• Regular• GPU-Friendly
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3-D Collision Grid: Advantage
A2
A1 A3
Obstacle
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Collision Test
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CP1 CP2
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? Cell checked for collision
rDistance between collision check points
An Agent
pn Agent destination
Path taken
Collision test radius around CP
CPn Collision check point along the path
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Collision Avoidance
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p1A3
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+α
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+β
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Rotating the Gradient
0º15º45º80º90º120º
Rotation
A1
Goal
A1
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CG-UFRGS Finding a Free Route
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Outline
• Related Work• Background• Global Navigation
– Hierarchical Computation of Distances
• Local Navigation– Collision Grid– Finding an Unobstructed Direction
• Results• Discussion• Conclusion
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Results
Tris: 20 000Verts: 10 000FPS: 30Agents: 512Grid Res: 1283
The agent color indicates the goal it is afterAfter the agent reaches a goal it moves to another
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Tris: 10 000Verts: 5 000FPS: 30Agents: 512Grid Res: 1283
The agent color indicates the goal it is afterAfter the agent reaches a goal it moves to another
Results
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Performance
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Outline
• Related Work• Background• Global Navigation
– Hierarchical Computation of Distances
• Local Navigation– Collision Grid– Finding an Unobstructed Direction
• Results• Discussion• Conclusion
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Discussion• Non Collision Free– First step towards the solution
• Only collision avoidance• Collision Grid– Non smooth response– False positive
A2
A1
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Conclusion
• Multi-agent navigation on non-planar surfaces
• Multi-resolution distance computation
• GPU-based approach for collision avoidance
• CPU/GPU path planning pipeline
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Questions?
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Performance