CG-UFRGS

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

1 2 3

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

f1

r1A1 AmM Agents A2 A3 A4 ...

Path PlanningPath Planning

Path Planning

...f4

r2

f3

r3

f2

r1

f2

r2

f3

r2

f3

r1

M Threads

CPU GPU

Available

f4

r3

f1

r1

f4

r2

f3

r3

f2

r1

f2

r2

f3

r2

f3

r1

Distance Fields Destination Resolution

To be Processed

Fd

rr

Not Ready

fd

rr

Ready fd

rr

First...

Fd

rr

Last

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

A1

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CP1 CP2

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CP3

CP4

CP5

CP6

CP0

CP7

? 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

A1

p1A3

A2

+α

-α

+2α

-2α

+β

-β

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Rotating the Gradient

0º15º45º80º90º120º

Rotation

A1

Goal

A1

CG-UFRGS Finding a Free Route

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A2

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A2

A1

p1

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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