Multi-domain real-time planning in dynamic environments

This paper presents a real-time planning framework for multi-character navigation that enables the use of multiple heterogeneous problem domains of differing complexities for navigation in large, complex, dynamic virtual environments. The original navigation problem is decomposed into a set of smaller problems that are distributed across planning tasks working in these different domains. An anytime dynamic planner is used to efficiently compute and repair plans for each of these tasks, while using plans in one domain to focus and accelerate searches in more complex domains. We demonstrate the benefits of our framework by solving many challenging multi-agent scenarios in complex dynamic environments requiring space-time precision and explicit coordination between interacting agents, by accounting for dynamic information at all stages of the decision-making process.

[1]  Tsai-Yen Li,et al.  Space‐time planning in changing environments : using dynamic objects for accessibility , 2012, Comput. Animat. Virtual Worlds.

[2]  Jessica K. Hodgins,et al.  Construction and optimal search of interpolated motion graphs , 2007, ACM Trans. Graph..

[3]  Céline Loscos,et al.  Intuitive crowd behavior in dense urban environments using local laws , 2003, Proceedings of Theory and Practice of Computer Graphics, 2003..

[4]  Maxim Likhachev,et al.  D*lite , 2002, AAAI/IAAI.

[5]  Petros Faloutsos,et al.  Egocentric affordance fields in pedestrian steering , 2009, I3D '09.

[6]  Dinesh Manocha,et al.  Real-time navigation of independent agents using adaptive roadmaps , 2007, VRST '07.

[7]  Okan Arikan,et al.  Interactive motion generation from examples , 2002, ACM Trans. Graph..

[8]  Lucas Kovar,et al.  Fast and accurate goal-directed motion synthesis for crowds , 2005, SCA '05.

[9]  Ming C. Lin,et al.  Motion planning and autonomy for virtual humans , 2008, SIGGRAPH '08.

[10]  Alex J. Champandard,et al.  DHPA* and SHPA*: Efficient Hierarchical Pathfinding in Dynamic and Static Game Worlds , 2010, AIIDE.

[11]  Brian Tanner,et al.  Hierarchical Heuristic Search Revisited , 2005, SARA.

[12]  Daniel Thalmann,et al.  Crowd Simulation , 2007, Wiley Encyclopedia of Computer Science and Engineering.

[13]  Jean-Claude Latombe,et al.  Randomized Kinodynamic Motion Planning with Moving Obstacles , 2002, Int. J. Robotics Res..

[14]  Sebastian Thrun,et al.  ARA*: Anytime A* with Provable Bounds on Sub-Optimality , 2003, NIPS.

[15]  Maxim Likhachev,et al.  Path Planning with Adaptive Dimensionality , 2011, SOCS.

[16]  Craig W. Reynolds.  Flocks, herds, and schools: a distributed behavioral model , 1998 .

[17]  Petros Faloutsos,et al.  Interactive motion correction and object manipulation , 2007, SIGGRAPH '08.

[18]  Adi Botea,et al.  Near Optimal Hierarchical Path-Finding , 2004, J. Game Dev..

[19]  Manfred Lau,et al.  Behavior planning for character animation , 2005, SCA '05.

[20]  Norman I. Badler,et al.  Virtual Crowds: Methods, Simulation, and Control (Synthesis Lectures on Computer Graphics and Animation) , 2008 .

[21]  Dinesh Manocha,et al.  Interactive motion planning using hardware-accelerated computation of generalized Voronoi diagrams , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[22]  Glenn Reinman,et al.  A modular framework for adaptive agent-based steering , 2011, SI3D.

[23]  Matthias Zwicker,et al.  Real-time planning for parameterized human motion , 2008, SCA '08.

[24]  Jur P. van den Berg,et al.  Anytime path planning and replanning in dynamic environments , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[25]  Sebastian Thrun,et al.  Anytime Dynamic A*: An Anytime, Replanning Algorithm , 2005, ICAPS.

[26]  Maxim Likhachev,et al.  SIPP: Safe interval path planning for dynamic environments , 2011, 2011 IEEE International Conference on Robotics and Automation.

[27]  Petros Faloutsos,et al.  Interactive motion correction and object manipulation , 2008, SIGGRAPH Classes.

[28]  Nathan R. Sturtevant,et al.  A Comparison of High-Level Approaches for Speeding Up Pathfinding , 2010, AIIDE.

[29]  Alberto Lacaze.  Hierarchical planning algorithms , 2002, SPIE Defense + Commercial Sensing.

[30]  Jesfis Peral,et al.  Heuristics -- intelligent search strategies for computer problem solving , 1984 .

[31]  Dinesh Manocha,et al.  Reciprocal Velocity Obstacles for real-time multi-agent navigation , 2008, 2008 IEEE International Conference on Robotics and Automation.

[32]  Benjamin W. Wah,et al.  Wiley Encyclopedia of Computer Science and Engineering , 2009, Wiley Encyclopedia of Computer Science and Engineering.

[33]  Dinesh Manocha,et al.  Interactive navigation of multiple agents in crowded environments , 2008, I3D '08.

[34]  Robert C. Holte,et al.  Hierarchical A*: Searching Abstraction Hierarchies Efficiently , 1996, AAAI/IAAI, Vol. 1.

[35]  Marcelo Kallmann.  Shortest paths with arbitrary clearance from navigation meshes , 2010, SCA '10.

[36]  Sung Yong Shin,et al.  Planning biped locomotion using motion capture data and probabilistic roadmaps , 2003, TOGS.

[37]  Sergey Levine,et al.  Space-time planning with parameterized locomotion controllers , 2011, TOGS.

[38]  Nathan R. Sturtevant,et al.  Graph Abstraction in Real-time Heuristic Search , 2007, J. Artif. Intell. Res..

[39]  Thierry Fraichard,et al.  Trajectory planning in a dynamic workspace: a 'state-time space' approach , 1998, Adv. Robotics.

[40]  Norman I. Badler,et al.  Virtual Crowds: Methods, Simulation, and Control , 2008, Virtual Crowds: Methods, Simulation, and Control.

[41]  Glenn Reinman,et al.  Footstep navigation for dynamic crowds , 2011, SI3D.

[42]  Jehee Lee,et al.  Deformable Motion: Squeezing into Cluttered Environments , 2011, Comput. Graph. Forum.

[43]  Stéphane Donikian,et al.  Crowd of Virtual Humans: a New Approach for Real Time Navigation in Complex and Structured Environments , 2004, Comput. Graph. Forum.

[44]  Adrien Treuille,et al.  Continuum crowds , 2006, ACM Trans. Graph..

[45]  Glenn Reinman,et al.  Scenario space: characterizing coverage, quality, and failure of steering algorithms , 2011, SCA '11.

[46]  Sébastien Paris,et al.  Pedestrian Reactive Navigation for Crowd Simulation: a Predictive Approach , 2007, Comput. Graph. Forum.

[47]  Roland Geraerts,et al.  Real‐time density‐based crowd simulation , 2012, Comput. Animat. Virtual Worlds.