{"action":"created","comment":{"url":"https://api.github.com/repos/ompl/ompl/pulls/comments/29157200","id":29157200,"diff_hunk":"@@ -217,3 +229,260 @@ void ompl::RNG::eulerRPY(double value[3])\n     value[1] = acos(1.0 - 2.0 * uni_()) - boost::math::constants::pi<double>() / 2.0;\n     value[2] = boost::math::constants::pi<double>() * (-2.0 * uni_() + 1.0);\n }\n+\n+\n+void ompl::RNG::uniformNormalVector(unsigned int n, double value[])\n+{\n+    //Construct the Boost distribution and generator. These would ideally be at the class level, but the spherical distribution requires dimension at construction\n+    boost::uniform_on_sphere<> uniformSphereDist(n);\n+    boost::variate_generator<boost::mt19937&, boost::uniform_on_sphere<> > normalizedVector(generator_, uniformSphereDist);\n+\n+    //A temporary vector for the BOOST return value\n+    std::vector<double> rVector;\n+\n+    //Generate a random value, the variate_generator returns a std::vector\n+    rVector = normalizedVector();\n+\n+    //Copy into the array, wish I knew of a better way than having used the temporary vector...","path":"src/ompl/util/src/RandomNumbers.cpp","position":null,"original_position":37,"commit_id":"8b4f66927b5e4ace662d419d1f17b7def84082dd","original_commit_id":"248350cd12a52df5001b64392f43cfd6785f82e0","user":{"login":"gammell","id":5250910,"avatar_url":"https://avatars.githubusercontent.com/u/5250910?v=3","gravatar_id":"","url":"https://api.github.com/users/gammell","html_url":"https://github.com/gammell","followers_url":"https://api.github.com/users/gammell/followers","following_url":"https://api.github.com/users/gammell/following{/other_user}","gists_url":"https://api.github.com/users/gammell/gists{/gist_id}","starred_url":"https://api.github.com/users/gammell/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gammell/subscriptions","organizations_url":"https://api.github.com/users/gammell/orgs","repos_url":"https://api.github.com/users/gammell/repos","events_url":"https://api.github.com/users/gammell/events{/privacy}","received_events_url":"https://api.github.com/users/gammell/received_events","type":"User","site_admin":false},"body":"Thanks, I believe I got such an implementation working.","created_at":"2015-04-27T15:30:52Z","updated_at":"2015-04-27T15:30:52Z","html_url":"https://github.com/ompl/ompl/pull/49#discussion_r29157200","pull_request_url":"https://api.github.com/repos/ompl/ompl/pulls/49","_links":{"self":{"href":"https://api.github.com/repos/ompl/ompl/pulls/comments/29157200"},"html":{"href":"https://github.com/ompl/ompl/pull/49#discussion_r29157200"},"pull_request":{"href":"https://api.github.com/repos/ompl/ompl/pulls/49"}}},"pull_request":{"url":"https://api.github.com/repos/ompl/ompl/pulls/49","id":34047571,"html_url":"https://github.com/ompl/ompl/pull/49","diff_url":"https://github.com/ompl/ompl/pull/49.diff","patch_url":"https://github.com/ompl/ompl/pull/49.patch","issue_url":"https://api.github.com/repos/ompl/ompl/issues/49","number":49,"state":"open","locked":false,"title":"Informed Sampling","user":{"login":"gammell","id":5250910,"avatar_url":"https://avatars.githubusercontent.com/u/5250910?v=3","gravatar_id":"","url":"https://api.github.com/users/gammell","html_url":"https://github.com/gammell","followers_url":"https://api.github.com/users/gammell/followers","following_url":"https://api.github.com/users/gammell/following{/other_user}","gists_url":"https://api.github.com/users/gammell/gists{/gist_id}","starred_url":"https://api.github.com/users/gammell/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gammell/subscriptions","organizations_url":"https://api.github.com/users/gammell/orgs","repos_url":"https://api.github.com/users/gammell/repos","events_url":"https://api.github.com/users/gammell/events{/privacy}","received_events_url":"https://api.github.com/users/gammell/received_events","type":"User","site_admin":false},"body":"This is the idea of informed sampling generalized to different optimization objectives. There is a generic rejection sampler that would work for any objective, and a direct sampling technique for path length (as derived in the Informed RRT* paper).\r\n\r\nThese samplers are applicable to any planner and are required for Informed RRT* and BIT*, though neither of those algorithms are included in this commit. \r\n\r\nThere are a couple areas where I would really appreciate input on design decisions, so I've put some comments inline about that. As soon as we work through this, I'll submit PRs for Informed RRT* and BIT*.\r\n\r\nThanks in 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