{"id":34,"date":"2020-09-28T20:02:25","date_gmt":"2020-09-28T20:02:25","guid":{"rendered":"http:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/?page_id=34"},"modified":"2021-10-11T16:31:47","modified_gmt":"2021-10-11T20:31:47","slug":"project-management","status":"publish","type":"page","link":"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/project-management\/","title":{"rendered":"Project Management"},"content":{"rendered":"\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link\" href=\"#schedules\">Schedules<\/a><\/div>\n\n\n\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link\" href=\"#tests\">Test Plans<\/a><\/div>\n\n\n\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link\" href=\"#parts\">Parts List<\/a><\/div>\n\n\n\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link\" href=\"#issues\">Issues Log<\/a><\/div>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"schedules\">Schedules<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Gantt Chart<\/h3>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"792\" height=\"1024\" src=\"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/10\/Gantt-Fall.drawio-792x1024.png\" alt=\"\" class=\"wp-image-748\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/10\/Gantt-Fall.drawio-792x1024.png 792w, https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/10\/Gantt-Fall.drawio-232x300.png 232w, https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/10\/Gantt-Fall.drawio-768x993.png 768w, https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/10\/Gantt-Fall.drawio.png 950w\" sizes=\"auto, (max-width: 792px) 100vw, 792px\" \/><\/figure><\/div>\n\n\n\n<p class=\"has-text-align-center\">Gantt chart for fall semester showing schedules for work packages<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Presenters<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">Spring<\/h4>\n\n\n\n<p>Sensors and Motors Control Lab: Dan Bronstein<\/p>\n\n\n\n<p>Progress Review 1: Ben Kolligs<\/p>\n\n\n\n<p>Progress Review 2: Kelvin Kang<\/p>\n\n\n\n<p>Progress Review 3: Jacqueline Liao<\/p>\n\n\n\n<p>Progress Review 4: Dan Bronstein<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Fall<\/h4>\n\n\n\n<p>Progress Review 7: Dan Bronstein<\/p>\n\n\n\n<p>Progress Review 8: Kelvin Kang<\/p>\n\n\n\n<p>Progress Review 9: Ben Kolligs<\/p>\n\n\n\n<p>Progress Review 10: Jacqueline Liao<\/p>\n\n\n\n<p>Progress Review 11: Dan Bronstein<\/p>\n\n\n\n<hr class=\"wp-block-separator\" \/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"tests\">Test Plans<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Spring Validation<\/h3>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"702\" src=\"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/03\/Screen-Shot-2021-03-11-at-11.27.01-AM-1024x702.png\" alt=\"\" class=\"wp-image-404\" srcset=\"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/03\/Screen-Shot-2021-03-11-at-11.27.01-AM-1024x702.png 1024w, https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/03\/Screen-Shot-2021-03-11-at-11.27.01-AM-300x206.png 300w, https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/03\/Screen-Shot-2021-03-11-at-11.27.01-AM-768x527.png 768w, https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-content\/uploads\/sites\/51\/2021\/03\/Screen-Shot-2021-03-11-at-11.27.01-AM.png 1056w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<p class=\"has-text-align-center\">Graphical depiction of spring validation setup. Each number corresponds to the same step in &#8220;Procedure&#8221; listed below.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Goal: <\/h4>\n\n\n\n<p>Showcase our complete hardware along with the basic functionalities of our control, situation awareness, and human detection subsystems in a well-lit and smokeless room.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Location:<\/h4>\n\n\n\n<p>NSH Basement, CMU, Pittsburgh, PA<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Environment:<\/h4>\n\n\n\n<p>A well-lit room no smaller than 10m<sup>2<\/sup> with no smoke in the room.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Equipment:<\/h4>\n\n\n\n<p>Dragoon, visualizer, WiFi network, indoor room, room geometry\/obstacle proxies(cardboard boxes, furniture, trash bins etc.), human body, external light source<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Demonstrations:<\/h4>\n\n\n\n<ol class=\"wp-block-list\"><li><strong>Power and Startup<\/strong><ul><li>Procedure: Operator turns on robot and visualizer, then sets robot at the entrance to the room<\/li><\/ul><ul><li> Validation:<ul><li>The robot connects to the remote control<\/li><li>Jetson AGX turns on and connects to RealSense and Seek&nbsp;<\/li><li>RealSense depth and RGB, Seek Thermal streams operational and stream to AGX<\/li><li>VLP-16 starts scanning, Cartographer begins mapping using VLP-16 and RealSense IMU<\/li><li>Visualizer turns on and begins to display 2D map and RGB stream at 10Hz (<strong>M.P.4<\/strong>)<\/li><\/ul><\/li><\/ul><\/li><li><strong>Locomotion<\/strong><ul><li>Procedure: Operator moves robot forwards, backwards, using remote control at a max speed of 0.5 m\/s and can turn about its location<\/li><\/ul><ul><li>Validation:<ul><li>Robot moves forwards, backwards, at a min of 0.5 m\/s and turns in place at a speed of 18 degrees per second (<strong>M.P.5<\/strong>)<\/li><\/ul><\/li><\/ul><\/li><li><strong>SLAM<\/strong><ul><li>Procedure: Operator moves robot at a max speed of 0.2 m\/s through the obstacles in the room for at least 5 minutes using the 2D map and RGB stream displayed on the visualizer<\/li><li>Validation:<ul><li>2D map of room for up to 10m from the robot is displayed and updated on visualizer; the shape of major obstacles are captured in the map (<strong>M.P.3<\/strong>)<\/li><li>The position of the robot is displayed on a 2D map on the visualizer<\/li><\/ul><\/li><\/ul><\/li><li><strong>Basic Human Detection<\/strong><ul><li>Procedure: Robot detects and localizes human<\/li><li>Validation:<ul><li>The robot detects and localizes human 8m away within 5 seconds of complete, unobstructed entrance into the RGB and Seek FOV with 75% accuracy (<strong>M.P.0, M.P.1<\/strong>)<\/li><li>The location of the human is displayed on a 2D map on the visualizer. Check that the centroidal accuracy of the bounding box is within 1 foot relative to the mapped room geometry<\/li><\/ul><\/li><\/ul><\/li><\/ol>\n\n\n\n<p><br><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Fall Validation<\/h3>\n\n\n\n<h4 class=\"wp-block-heading\">Goal:<\/h4>\n\n\n\n<p>Demonstrate that Dragoon can autonomously navigate and operate in a dimly lit room and is able to determine the presence and location of a partially occluded human, which is displayed real-time on a 2D map.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Location: <\/h4>\n\n\n\n<p>NSH Basement, CMU, Pittsburgh, PA<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Environment:<\/h4>\n\n\n\n<p>A dimly-lit room no smaller than 10m<sup>2<\/sup>.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Equipment:<\/h4>\n\n\n\n<p>Dragoon, visualizer, WiFi network, indoor room, room geometry\/obstacle proxies(cardboard boxes, furniture, trash bins etc.), human body, luxmeter<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Demonstrations:<\/h4>\n\n\n\n<ol class=\"wp-block-list\"><li><strong><strong>Human Detection and Localization Test<\/strong><\/strong><ul><li>Procedure: <ul><li>A human subject is placed in a supine position 3-7m directly in front of the robot, in profile view<\/li><li>An occluding obstacle is placed blocking 0-25% of the subject<\/li><li>The location of the detected human on the visualized map is noted<\/li><li>Steps i-iii are repeated with varying quality of occlusion, subject pose, distance from the robot and level of ambient lighting<\/li><\/ul><\/li><li>Validation:<ul><li>Robot detects and localizes human who is at maximum 25% occluded 3m away in minimum 150 lux low-visibility lighting (<strong>M.P.1, M.P.2, M.N.0<\/strong>)<\/li><li>The robot detects and localizes non-occluded humans 7m away (<strong>M.P.1, M.P.2, M.N.0<\/strong>)<\/li><li>Human detected in real-time<\/li><li>Accurate location (within 0.5m radius) of human(s) displayed on 2D map on visualizer in real-time (<strong>M.P.3, M.F.3<\/strong>)<\/li><\/ul><\/li><\/ul><\/li><li><strong><strong>Autonomous Navigation Test<\/strong><\/strong><ul><li>Procedure: <ul><li>Place robot in a simulated disaster scenario and let it generate paths<\/li><li>Command the robot to follow a generated path<\/li><\/ul><\/li><\/ul><ul><li>Validation:<ul><li>Robot plans paths that avoid obstacles and generates goals in unexplored territory<\/li><li>Robot follows the generated path<\/li><\/ul><\/li><\/ul><\/li><li><strong><strong>Autonomous Search and Rescue Test:<\/strong><\/strong><ul><li>Procedure: <ul><li>Place robot in a simulated 30m<sup>2 <\/sup>disaster scenario, with 2 human \u2018victims\u2019, and give the robot a signal to begin autonomous exploration<\/li><\/ul><\/li><\/ul><ul><li>Validation:<ul><li>Robot gives signal that exploration is done within 5 minutes (<strong>M.P.8, M.F.7<\/strong>)<\/li><li>RGB stream and 2D map of room for up to 10m from the robot is displayed and updated on visualizer; the shape of major obstacles are captured in the map (<strong>M.P.2, M.P.3, M.N.0<\/strong>)<\/li><li>2D map is displayed and visualized in real-time (<strong>M.P.3<\/strong>)<\/li><li>Validation of the <strong>Human Detection and Localization Test <\/strong>for both victims<\/li><\/ul><\/li><\/ul><\/li><\/ol>\n\n\n\n<h3 class=\"wp-block-heading\">Fall Progress Review Milestones<\/h3>\n\n\n\n<ol class=\"wp-block-list\"><li><strong>PR 1 (9\/15)<\/strong><ul><li>IR human detection Integrated into pipeline<\/li><li>Local planner\/obstacle avoidance implemented<\/li><\/ul><\/li><li><strong>PR 2 (9\/29)<\/strong><ul><li>DevOps for retraining RGB and IR networks complete<\/li><li>Architecture for global planner complete<\/li><\/ul><\/li><li><strong>PR 3 (10\/13)<\/strong><ul><li>Global planner implementation complete<\/li><li>Initial retraining of RGB and IR networks complete<\/li><\/ul><\/li><li><strong>PR 4 (10\/27)<\/strong><ul><li>Global and local planners integrated with each other<\/li><li>Retraining of weights for supine positions and dark conditions complete<\/li><\/ul><\/li><li><strong>PR 5 (11\/10)<\/strong><ul><li>Entire planning stack integrated with full system, including human machine interface<\/li><\/ul><ul><li>Retraining of weights finalized and integrated with full system<\/li><\/ul><\/li><\/ol>\n\n\n\n<p><a href=\"https:\/\/drive.google.com\/file\/d\/1x3FFwU0HRuz6iKdTin2bOOgfHCk__vHx\/view?usp=sharing\" target=\"_blank\" rel=\"noreferrer noopener\">Full Fall Semester Test Plan<\/a> (external link)<\/p>\n\n\n\n<hr class=\"wp-block-separator\" \/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"parts\">Parts List<\/h2>\n\n\n\n<p><a href=\"https:\/\/docs.google.com\/spreadsheets\/d\/1JrGDeQ6gFunA-E712DvJ-uJ_JTeMhQvnFN2ayrbuEOE\/edit?usp=sharing\" target=\"_blank\" rel=\"noreferrer noopener\">HOWDE Parts List<\/a> (external link)<\/p>\n\n\n\n<hr class=\"wp-block-separator\" \/>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"issues\">Issues Log<\/h2>\n\n\n\n<p><a href=\"https:\/\/docs.google.com\/spreadsheets\/d\/1WnFGbafFsJkxpRm1P9HfA-FyPPrAaPIyjyw_v2Yq3to\/edit?usp=sharing\" target=\"_blank\" rel=\"noreferrer noopener\">HOWDE Issues Log<\/a> (external link)<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Schedules Gantt Chart Gantt chart for fall semester showing schedules for work packages Presenters Spring Sensors and Motors Control Lab: Dan Bronstein Progress Review 1: Ben Kolligs Progress Review 2: Kelvin Kang Progress Review 3: Jacqueline Liao Progress Review 4: Dan Bronstein Fall Progress Review 7: Dan Bronstein Progress Review 8: Kelvin Kang Progress Review<br \/><a class=\"moretag\" href=\"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/project-management\/\">+ Read More<\/a><\/p>\n","protected":false},"author":236,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-34","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-json\/wp\/v2\/pages\/34","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-json\/wp\/v2\/users\/236"}],"replies":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-json\/wp\/v2\/comments?post=34"}],"version-history":[{"count":42,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-json\/wp\/v2\/pages\/34\/revisions"}],"predecessor-version":[{"id":753,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-json\/wp\/v2\/pages\/34\/revisions\/753"}],"wp:attachment":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2021teamb\/wp-json\/wp\/v2\/media?parent=34"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}