Robot Motion Planning
Coordinating Multiple Robots with Kinodynamic Constraints Along Specified Paths
International Journal of Robotics Research
Populating virtual environments with crowds
Proceedings of the 2006 ACM international conference on Virtual reality continuum and its applications
Planning Algorithms
Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions
Transportation Science
Virtual Crowds: Methods, Simulation, and Control (Synthesis Lectures on Computer Graphics and Animation)
ClearPath: highly parallel collision avoidance for multi-agent simulation
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Experiment-based modeling, simulation and validation of interactions between virtual walkers
Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
An Optimality Principle Governing Human Walking
IEEE Transactions on Robotics
When a couple goes together: walk along steering
MIG'11 Proceedings of the 4th international conference on Motion in Games
Politeness improves interactivity in dense crowds
Computer Animation and Virtual Worlds
Tracking with a mixed continuous-discrete Conditional Random Field
Computer Vision and Image Understanding
The Visual Computer: International Journal of Computer Graphics
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In this paper, we present a new trajectory planning algorithm for virtual humans. Our approach focuses on implicit cooperation between multiple virtual agents in order to share the work of avoiding collisions with each other. Specifically, we extend recent work on multi-robot planning to better model how humans avoid collisions by introducing new parameters that model human traits, such as reaction time and biomechanical limitations. We validate this new model based on data of real humans walking captured by the Locanthrope project [12]. We also show how our model extends to complex scenarios with multiple agents interacting with each other and avoiding nearby obstacles.