{"id":745,"date":"2019-11-09T01:21:44","date_gmt":"2019-11-09T01:21:44","guid":{"rendered":"http:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/?page_id=745"},"modified":"2019-11-09T01:32:26","modified_gmt":"2019-11-09T01:32:26","slug":"risks","status":"publish","type":"page","link":"https:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/risks\/","title":{"rendered":"Risk Updates"},"content":{"rendered":"

Below are the updated risks:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n
N<\/b><\/td>\nRequirement<\/b><\/td>\nRisk and Description<\/b><\/td>\nRisk Reduction Plan \/ Mitigation Results<\/b><\/td>\nL<\/b><\/td>\nC<\/b><\/td>\nType<\/b><\/td>\n<\/tr>\n
1<\/span><\/td>\nM.P.13<\/b><\/td>\nSystem Does not Work in Real-Time<\/b><\/p>\n

A certain subsystem(s)<\/span><\/p>\n

\u00a0creates bottlenecks<\/span><\/td>\n

1. Find techniques to perform memory management for each algorithm<\/span><\/p>\n

2. Use high performance processors (We bought an high-end system and received NVIDIA Titan V)<\/span><\/td>\n

5<\/span><\/td>\n5<\/span><\/td>\nTechnical<\/span><\/td>\n<\/tr>\n
2<\/span><\/td>\nM.P.2, M.P.3, M.P.4<\/b><\/td>\nGPU Memory Management<\/b><\/p>\n

There is a GPU memory<\/span><\/p>\n

limitation to 12GB<\/span><\/td>\n

1. Optimize perception pipeline, keeping in mind GPU memory limitations from beginning<\/span><\/p>\n

2. Plan on installing a second GPU on the system<\/span><\/td>\n

5<\/span><\/td>\n4<\/span><\/td>\nTechnical \/ Resources<\/span><\/td>\n<\/tr>\n
3<\/span><\/td>\n—<\/b><\/td>\nTeam Members Work at Different Pace<\/b><\/p>\n

This might create delays in integration<\/span><\/td>\n

1. Meet twice a week to ensure no one is lagging behind their goals<\/span><\/p>\n

2. Track progress on Notion<\/span><\/p>\n

3. Communicate \/ resolve issues on Slack<\/span><\/td>\n

5<\/span><\/td>\n3<\/span><\/td>\nSchedule<\/span><\/td>\n<\/tr>\n
4<\/span><\/td>\nM.P.12 – M.P.14<\/b><\/td>\nInterfacing Sensor with RC car<\/b><\/p>\n

ROS integration of sensors and driver availability for ARM architecture<\/span><\/td>\n

1. Found FlyCapture ARM drivers and interfaced PointGrey camera successfully<\/span><\/p>\n

2. Built Ti mmWave RADAR drivers and ROS packages from source for ARM architecture<\/span><\/td>\n

4<\/span><\/td>\n4<\/span><\/td>\nTechnical \/ Resources<\/span><\/td>\n<\/tr>\n
5<\/span><\/td>\nM.P.12 – M.P.14<\/b><\/td>\nHardware Failure or Damage<\/b><\/p>\n

Critical hardware components such as sensors fail or get damaged<\/span><\/td>\n

1. Plan the budget to accommodate repairs<\/span><\/p>\n

2. Already have backup components, additional camera and RADAR sensors<\/span><\/p>\n

3. Ordered a secondary RC car<\/span><\/td>\n

3<\/span><\/td>\n5<\/span><\/td>\nTechnical \/ Cost<\/span><\/td>\n<\/tr>\n
6<\/span><\/td>\nM.P.12 – M.P.14<\/b><\/td>\nPerception pipeline doesn’t work\u00a0<\/b>online on RC car<\/b><\/p>\n

RC car’s compute is not enough to run\u00a0<\/span>the perception algorithms<\/span><\/td>\n

1. We ordered new on-board GPU for RC car to process perception and sensor fusion pipeline in real-time.<\/span><\/td>\n5<\/span><\/td>\n4<\/span><\/td>\nTechnical\u00a0<\/span><\/td>\n<\/tr>\n
7\u00a0<\/span><\/td>\nM.P.06 – M.P.10<\/b><\/td>\nError propagation further in pipeline<\/b><\/p>\n

Perception pipeline adds uncertainty in sensor fusion and prediction pipeline<\/span><\/td>\n

1.We designed our requirements carefully to compensate for the margin of error for every pipeline.<\/span><\/td>\n2<\/span><\/td>\n4<\/span><\/td>\nTechnical\u00a0<\/span><\/td>\n<\/tr>\n
8<\/span><\/td>\n—<\/b><\/td>\nOverambitious Requirements<\/b> – We are unable to meet our original requirements<\/span><\/td>\n\n
    \n
  1. Revisit the requirements every week and plan work accordingly<\/span><\/li>\n
  2. Use off-the-shelf algorithms\u00a0<\/span><\/li>\n<\/ol>\n<\/td>\n
3<\/span><\/td>\n4<\/span><\/td>\nSchedule\/Technical\u00a0<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n","protected":false},"excerpt":{"rendered":"

Below are the updated risks: N Requirement Risk and Description Risk Reduction Plan \/ Mitigation Results L C Type 1 M.P.13 System […]<\/p>\n","protected":false},"author":178,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-745","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/wp-json\/wp\/v2\/pages\/745","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/wp-json\/wp\/v2\/users\/178"}],"replies":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/wp-json\/wp\/v2\/comments?post=745"}],"version-history":[{"count":9,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/wp-json\/wp\/v2\/pages\/745\/revisions"}],"predecessor-version":[{"id":756,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/wp-json\/wp\/v2\/pages\/745\/revisions\/756"}],"wp:attachment":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2018teama\/wp-json\/wp\/v2\/media?parent=745"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}