abhranildas/Integrate-and-Classify-Normal-Distributions

Kris' changes

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  • Classify with ray_scan region, i.e. add samp_correct to example.

  • Add the line example with ray_scan, quad (gx2) and fun alternatives. See how different the results are.

  • Perhaps add something to the performance section about the above comparison: Re-define relative diff. in terms of ray-scan result. Make two columns, rel. diff and time, and sub-columns for each method, including fun. NOPE

  • Add fun to fig. 4a. NOPE

  • Maybe in ms text, add: for example, the ray_scan function of a line at y=k returns...

  • Compare two examples in demo: combining the circle regions using a function, vs ray-scanning quads, then using the combination operators. The second ought to be more accurate.

  • Then add back the text for these domain combination operations in ms, to say why they are useful.

  • Add set operation example figure to the bottom of 2d.

  • Add this in the performance section to compare between ray-scan and fun. NOPE

  • Documentation for custom ray_scan function etc. init_sign is at -infty.

  • Go through his e-mail again.

  • C++/MEX implementation

  • Add topics to intro: robotics, chance constrained programming/planning, probabilistic safety, risk-aware planning, add his citations.

  • Mention to Kris that I acknowledged him