{"id":112,"date":"2024-03-17T03:59:58","date_gmt":"2024-03-17T03:59:58","guid":{"rendered":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/?p=112"},"modified":"2024-03-17T04:01:10","modified_gmt":"2024-03-17T04:01:10","slug":"alexs-report-for-3-16","status":"publish","type":"post","link":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/2024\/03\/17\/alexs-report-for-3-16\/","title":{"rendered":"Alex&#8217;s Report for 3\/16"},"content":{"rendered":"<p>This week I worked more on the trajectory prediction, with the ping pong balls, I finished the filtering of unrealistic trajectories and am now considering working on getting the trajectory that traveled the most distance. I don&#8217;t think that this component will be strictly necessary since filtering out unrealistic trajectories already works quite well. I also need to think about how to test this component of the system as well.<\/p>\n<p>I thought a lot about cup detection this week because it feels harder to do than ball detection. I am going to try mapping the 3d point cloud into a 3d &#8220;pixelated&#8221; space and then go layer by layer searching for circles. Alternatively, if that doesn&#8217;t work I could use a computer vision model to detect the cups based on the rgb vision rather than LIDAR vision, but I&#8217;m trying to get LIDAR vision to work properly.<\/p>\n<p>I&#8217;m almost done with the first iteration of the launching subsystem, I only need to obtain a 2 liter soda bottle to use as a pressure chamber and hook that up to our current pressure system.<\/p>\n<p>Next week I think I&#8217;m just going to focus on trying to get as much as I can done with the computer vision subsystem and I might ask one of my groupmates to look for\/buy the pressure container (a 2 liter soda bottle).<\/p>\n<p>This puts me around where I expect to be on the schedule.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This week I worked more on the trajectory prediction, with the ping pong balls, I finished the filtering of unrealistic trajectories and am now considering working on getting the trajectory that traveled the most distance. &#8230;<\/p>\n","protected":false},"author":875,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[8],"tags":[4],"_links":{"self":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/posts\/112"}],"collection":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/users\/875"}],"replies":[{"embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/comments?post=112"}],"version-history":[{"count":2,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/posts\/112\/revisions"}],"predecessor-version":[{"id":114,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/posts\/112\/revisions\/114"}],"wp:attachment":[{"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/media?parent=112"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/categories?post=112"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/course.ece.cmu.edu\/~ece500\/projects\/s24-teama8\/wp-json\/wp\/v2\/tags?post=112"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}