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Real-time Navigation of Independent Agents Using Adaptive Roadmaps

Real-time Navigation of Independent Agents Using Adaptive Roadmaps. Presenter: Robin van Olst. The Authors. Erik Andersen. Avneesh Sud. Russell Gayle. Dinesh Manocha. Stephen Guy. Ming Lin. Related work. Elastic Bands – Quinlan and Khatib, 1993 Elastic Roadmaps – Yang and Brock, 2006

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Real-time Navigation of Independent Agents Using Adaptive Roadmaps

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  1. Real-time Navigation of Independent Agents Using Adaptive Roadmaps Presenter: Robin van Olst

  2. The Authors Erik Andersen Avneesh Sud Russell Gayle Dinesh Manocha Stephen Guy Ming Lin

  3. Related work • Elastic Bands – Quinlan and Khatib, 1993 • Elastic Roadmaps – Yang and Brock, 2006 • Real-time path planning for virtual agents in dynamics environments – Sud et al., 2006 • Voronoi diagram generation using a GPU • Planning algorithms – LaValle, 2006 • Random sampling • Self-organized pedestrian crowd dynamics and design solutions – Helbing, 2003 • Local dynamics model (social forces)

  4. Introduction • Adaptive Elastic Roadmaps (AERO) • Global path planning method • Graph structure adapts to dynamic environments • Link bands • Local dynamics model • Augmented to AERO • Simulates a thousand of heterogeneous agents individually in real-time Movie time!

  5. Outline • Adaptive Elastic Roadmaps (AERO) • Model description • Navigation with AERO • Link bands • Local dynamics model • Behaviour model • Implementation and results • Assessment

  6. Adaptive Elastic Roadmaps (AERO) • Based on a Generalized Voronoi diagram • Provides good initial clearance • Computes proximity information

  7. AERO Representation • The Adaptive Elastic Roadmap • Consists of: • Milestones • Links • Particles • Is a guiding path for agents • Find with graph search algorithms (A*) • Obstacles may block a path • Forces are applied to AERO

  8. AERO Force Computation • Force on particles and milestones: • Internal forces: • Prevent unnecessary link deformation • Prevent roadmap drifting • External forces: • Respond to obstacle motion

  9. AERO Link Removal • Necessary when a link is blocked • Removal criteria • Physics-based • A link exceeds its stretching threshold • Geometric-based • The short distance to all obstacle is less than the largest radius assign to an agent

  10. AERO Link Addition • Repair removed links • Check removed links • Check disconnected milestones • Repair is biased towards the area in the wake of moving obstacles • Lazy and incremental • Explore for new paths • Uses random sampling • Movie!

  11. Outline • Adaptive Elastic Roadmaps (AERO) • Model description • Navigation with AERO • Link bands • Local dynamics model • Behaviour model • Implementation and results • Assessment

  12. AERO Link Bands • Region of free space close to the nearest link • Space provides a collision-free path • Path planning • Starts at the nearest link • Each link is assigned a weight: • Function of: link length, band width and the number of actors present on the band • Each is weighted • High α: choose shortest paths (used for slow agents) • High β: avoids narrow paths • High γ: choose less crowded paths (used for aggressive agents)

  13. AERO Navigation: Link Bands • Local dynamics simulation • Helbing’s social forces model: • Modified to add discomfort zones in front of moving obstacles • Repulsive forces are biased along the motion of obstacles

  14. AERO Behaviour Modeling • Agents can stand still, walk or jog • Depends on velocity • Uses non-parallel thresholds • Prevents oscillations • Aggressive agents prefer to jog • Higher maximum velocity

  15. Outline • Adaptive Elastic Roadmaps (AERO) • Model description • Navigation with AERO • Link bands • Local dynamics model • Behaviour model • Implementation and results • Assessment

  16. AERO Implementation • 3Ghz Pentium D CPU, 2GB RAM • NVIDIA GeForce 7900 GPU, 512MB • OpenGL • Optimizations • Spatial hash table of all entities and links • Efficient lookups and proximity computation • Voronoi diagram of all obstacles is computed • Scan a window to get all the obstacles within a certain range

  17. Results • Performance (in ms) • Cited in ‘Abnormal crowd behavior detection using social force model’ by Mehran et al.

  18. Outline • Adaptive Elastic Roadmaps (AERO) • Model description • Navigation with AERO • Link bands • Local dynamics model • Behaviour model • Implementation and results • Assessment

  19. Positive Points • Adapts to dynamic obstacles • Handles changes in free space connectivity • Relates to real humans? • Able to simulate a thousand independently moving heterogeneous agents in real-time • Efficient • No assumptions on motion

  20. Limitations • Unrealistic high-DoF human motion • Only 3-DoF motion supported • Computed paths may not be optimal • Convergence is not guaranteed • Agents may get stuck in local minima

  21. Negative Points • Agents require a goal • No wandering • No grouping • Does not relate to real humans • Video shows rapid changes in orientation • Probably not able to simulate denser crowds

  22. Suggestions • More efficient local dynamics model? • Complement method with: • Continuum Crowds’ discomfort fields • Navigational Fields’ directional preference

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