Class #7: Probabilistic Roadmaps (2/3) –
Sampling Strategies
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The Gaussian strategy (left) is intended to place milestones mostly near the obstacle boundary. The Bridge test (center) is aimed at producing a higher density of milestones in narrow passages. The visibility-based connection strategy (two figures on the right) is aimed at building coarser roadmaps, still with good coverage and connectivity properties.

• Topics
  - Multi-query vs. single-query sampling
  - Sampling vs. connection strategies
  - Multi-stage sampling
  - Obstacle-sensitive sampling
  - Narrow-passage sampling
  - Diffusion strategies
  - Delayed collision checking
  - Visibility-based connection
• Required Readings:
• Obstacle-sensitive and narrow-passage sampling:
  V. Boor, M.H. Overmars, A.F. van der Stappen. The Gaussian sampling strategy for probabilistic roadmap planners. Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1018-1023, 1999 [pdf].
  +
  D. Hsu, T. Jiang, J. Reif, and Z. Sun. The Bridge Test for Sampling Narrow Passages with Probabilistic Roadmap Planners. Proceedings of the IEEE International Conference on Robotics and Automation, Taipei, 2003. [pdf]
• Reduction of roadmap size (visibility-based connection):
  T. Siméon, J.P Laumond, and C. Nissoux. Visibility-Based Probabilistic Roadmaps for Motion Planning. Advanced Robotics J., 14(6), 2000 [ps] [pdf].
  
  
• Additional Readings:
• Another obstacle-sensitive sampling technique:
  N.M. Amato, O.B. Bayazit, L.K. Dale, C. Jones, D. Vallejo. OBPRM: An Obstacle-Based PRM for 3D Workspaces. Proc. Workshop on Algorithmic Foundations of Robotics (WAFR'98), March 1998, pp. 155-168. [pdf]
  
  
• Powerpoint slides:

o Introduction

o Paper 1

o Paper 2