Random number generation and quasi-Monte Carlo methods
Random number generation and quasi-Monte Carlo methods
Autonomous behaviors for interactive vehicle animations
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Planning Algorithms
Maneuver-based motion planning for nonlinear systems with symmetries
IEEE Transactions on Robotics
Path diversity is only part of the problem
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Motion planning with dynamics by a synergistic combination of layers of planning
IEEE Transactions on Robotics
Scalable precomputed search trees
MIG'10 Proceedings of the Third international conference on Motion in games
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A novel criterion is introduced for assessing the diversity of a collection of paths or trajectories. The main idea is the notion of survivability, which measures the likelihood that numerous paths are obstructed by the same obstacle. This helps to improve robustness with respect to collision, which is an important challenge in the design of real-time planning algorithms. Efficient algorithms are presented for computing the survivability criterion and for selecting a subset of paths that optimize survivability from a larger collection. The algorithms are implemented and solutions are illustrated for two different systems. Chi-square tests are used to show uniform coverage obtained by using the computed paths in a simple breadth-first search. Random obstacle placement is used to show superior robustness of these primitives compared to uniform sampling of the control space.