Unattractive traversable terrain is made impassable for particular characters. Grand Theft Auto IV by Rockstar North 2008. Jaklin et al. (Utrecht University).
Real-Time Path Planning in Heterogeneous Environments Norman Jaklin1 1 Utrecht 2 University
Atlas Cook IV2
Roland Geraerts1
University - Department of Information and Computing Sciences
of Texas at Austin - Institute for Computational Engineering and Sciences
Computer Animation and Social Agents 2013
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Motivation
Path planning method: MIRAN - Modified Indicative Routes and Navigation Motivation: start movie
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Problems with terrain-based path planning in current games and simulations
Inflexible solutions for handling individual terrain preferences Traversable areas treated as equal, independent of individual terrain preferences Unattractive traversable terrain is made impassable for particular characters
Grand Theft Auto IV by Rockstar North 2008
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More problems
Paths are often illogical and not visually convincing Unnecessary detours No smooth trajectories Unnatural clearance from obstacles Characters do not look ahead enough Obstacles or rough terrain is ignored
World of Warcraft by Blizzard Entertainment 2004 Jaklin et al. (Utrecht University)
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MIRAN - Modified Indicative Routes and Navigation
Input: A 2D polygonal environment Virtual characters with sets of individual region preferences An indicative route that roughly guides a character automatically computed or manually designed
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MIRAN - Modified Indicative Routes and Navigation
Output: A natural-looking path that gives the user control over the amount of smoothing is based on a character’s region preferences keeps clearance from obstacles avoids unnecessary detours can be computed in real-time
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The MIRAN method - Overview
Step 1: Compute reference point on the indicative route Step 2: Compute set of candidate attraction points Step 3: Pick best attraction point Step 4: Move character towards attraction point
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Two user-controlled parameters
The shortcut parameter σ The sampling distance d
indicative route
d character position
σ
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Step 1: Compute reference point r
ri := first closest point on the indicative route between former reference point ri−1 and former attraction point αi−1
indicative route αi−1 ri ri−1 xi
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Step 2: Compute set A of candidate attraction points
Visible points along the indicative route between ri and σi discretized with sampling distance d
goal
σi αi7 αi6
αi5 αi4 αi3
xi start
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αi2 ri αi1
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Step 3: Pick best attraction point α from A
Each line segment between x and αi is weighted with the underlying type of terrain and the curve length distance from r to αi . Lower terrain costs ⇒ lower weight αi further ahead on the indicative route ⇒ lower weight
goal
x α3 start
r
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α1
α2
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Step 4: Move character towards α
α1 α2 α3 x2
x3
x4
x1
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Forest example with two character profiles
Start Demo
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Experimental Results
Comparison with the Indicative Route Method (IRM) by Karamouzas et al. [2]
g
s
Overall scene size: 200 × 200 units shortcut parameter σ = 40 sampling distance d = 10 Running times: 4.66ms (MIRAN), 4.48ms (IRM) Jaklin et al. (Utrecht University)
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Open Research Questions and Future Extensions
Handle disc-shaped characters with variable radius in a better way Improve computation of indicative routes as input for MIRAN Extend terrain-based movement to local collision-avoidance routines Generalize MIRAN to (multi-layered) 3D environments with height information
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Thank You!
R. Geraerts. Planning short paths with clearance using Explicit Corridors. In Proceedings of the IEEE International Conference on Robotics and Automation, pages 1997–2004, 2010. I. Karamouzas, R. Geraerts, and M. Overmars. Indicative routes for path planning and crowd simulation. 4th International Conference on Foundations of Digital Games, pages 113–120, 2009. Jaklin et al. (Utrecht University)
