Class #7: Sampling Strategies for Probabilistic Roadmaps
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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. Workspace-based sampling (right) tries to predict narrow passage areas in configuration space from an analysis of the workspace.

• Topics
  - Multi-query vs. single-query sampling
  - Sampling vs. connection strategies
  - Workspace-based strategies
  - Filtering strategies
  - Adaptive strategies
  - Deformation strategies
• Required Readings:
• Examples of filtering strategies (Gaussian sampling and Bridge test):
  V. Boor, M.H. Overmars, A.F. van der Stappen. The Gaussian sampling strategy for probabilistic roadmap planners. Proc. IEEE Int. Conf. on Robotics and Automation, pp. 1018-1023, 1999 [pdf].
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  D. Hsu, T. Jiang, J. Reif, and Z. Sun. The Bridge Test for Sampling Narrow Passages with Probabilistic Roadmap Planners. Proc. IEEE Int. Conf. on Robotics and Automation, Taipei, 2003. [pdf]
• Example of workspace-based strategy:
  H. Kurniawati and D. Hsu. Workspace-Based Connectivity Oracle: An Adaptive Sampling Strategy for PRM Planning. In S. Akella et al., editors, Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR), Springer, 2006. [pdf].
  
  
• Powerpoint slides:

o Introduction

o Paper 1

o Paper 2