{"id":698,"date":"2024-05-03T16:08:52","date_gmt":"2024-05-03T16:08:52","guid":{"rendered":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/?page_id=698"},"modified":"2024-05-03T18:41:32","modified_gmt":"2024-05-03T18:41:32","slug":"component-testing","status":"publish","type":"page","link":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/documents\/component-testing\/","title":{"rendered":"Component Testing"},"content":{"rendered":"\n

At EmberEye, we take testing and validating our systems very seriously. When operating in extreme conditions like WildFire, the reliability and robustness of our system are of utmost importance, because a system failure can lead to the loss of valuable information to the operators which could be a matter of life and death.

Driven by this motivation, we push all our systems to the limit in various emulated\/real stress conditions to evaluate their performance.<\/p>\n\n\n\n

Hardware Subsystem<\/h2>\n\n\n\n

The developed aerial robotic platform designated “Phoenix” has been tested vigorously to ensure robust, reliable and repeatable performance. Post the complete systems integration on the AirFrame we performed verification tests as detailed below. These tests were broadly classified into:

Electrical Verification Test<\/strong>:<\/p>\n\n\n\n

\"\"<\/p>\n\n\n\n

Mechanical Verification Test<\/strong>:<\/p>\n\n\n\n

\"\"<\/p>\n\n\n\n

For details of the results of these tests please refer to PR#1<\/a>.<\/p>\n\n\n\n

Fire Perception Subsystem<\/h2>\n\n\n\n

The Fire Perception subsystem is at the heart of our overall system and is essential to generate valuable fire analytics to aid first responders with actionable insights. This section outlines all the tests associated with this submodule.<\/p>\n\n\n\n

Camera Calibration Verification Test<\/strong>:<\/p>\n\n\n\n

\"\"
Please refer to PR#2<\/a> for the results and specific details. <\/p>\n\n\n\n

Offline Fire Segmentation Test<\/strong>:<\/p>\"\"
Please refer to PR#2<\/a> for the results and specific details. <\/p>\n\n\n\n

Real-time Fire Segmentation Test<\/strong>:<\/p>\n\n\n\n

\"\"
Please refer to PR#3<\/a> for the results and specific details.<\/p>\n\n\n\n

Real-time Fire Localization Test (Static Drone)<\/strong>:<\/p>\n\n\n\n

\"\"
Please refer to PR#3<\/a> for the results and specific details.<\/p>\n\n\n\n

Real-time Fire Localization Test (In-Flight)<\/strong>:<\/p>\n\n\n\n

\"\"
Please refer to PR#4<\/a> for the results and specific details.<\/p>\n\n\n\n

State Estimation Subsystem<\/h2>\n\n\n\n

As our system is required to operate in GPS-denied\/degraded settings, we need a robust state estimation pipeline which uses an alternate modality. Furthermore, our mandatory non-functional requirement MN4<\/strong> requires us to rely only on passive sensing modalities which led us to converge to vision\/thermal-based state estimation. This section outlines the test(s) for the same.<\/p>\n\n\n\n

\"\"
Please refer to PR#3<\/a> and PR#4<\/a> for the results and specific details.<\/p>\n\n\n\n

Ground Control Station Subsystem<\/h2>\n\n\n\n

An integral part of our overall system. GCS is required for reliable high-bandwidth comms to the UAS for real-time transmission of all the fire analytics collected onboard the UAS. This section outlines the tests conducted to validate the efficacy of the same.<\/p>\n\n\n\n

\"\"
Please see more details about the GCS tests here<\/a>.

<\/p>\n","protected":false},"excerpt":{"rendered":"

At EmberEye, we take testing and validating our systems very seriously. When operating in extreme conditions like WildFire, the reliability and robustness of our system are of utmost importance, because a system failure can lead to the loss of valuable information to the operators which could be a matter of life and death. Driven by … Continue Reading<\/strong> <\/i><\/a><\/p>\n","protected":false},"author":350,"featured_media":0,"parent":41,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-698","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/wp-json\/wp\/v2\/pages\/698","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/wp-json\/wp\/v2\/users\/350"}],"replies":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/wp-json\/wp\/v2\/comments?post=698"}],"version-history":[{"count":6,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/wp-json\/wp\/v2\/pages\/698\/revisions"}],"predecessor-version":[{"id":739,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/wp-json\/wp\/v2\/pages\/698\/revisions\/739"}],"up":[{"embeddable":true,"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/wp-json\/wp\/v2\/pages\/41"}],"wp:attachment":[{"href":"https:\/\/mrsdprojects.ri.cmu.edu\/2024teamb\/wp-json\/wp\/v2\/media?parent=698"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}