{"id":37450,"date":"2020-02-08T09:41:15","date_gmt":"2020-02-08T14:41:15","guid":{"rendered":"https:\/\/www.opensource.im\/uncategorized\/artificial-intelligence-assists-in-the-study-of-autonomous-vehicle-performance-in-winter-conditions-vision-systems-design.php"},"modified":"2020-02-08T09:41:15","modified_gmt":"2020-02-08T14:41:15","slug":"artificial-intelligence-assists-in-the-study-of-autonomous-vehicle-performance-in-winter-conditions-vision-systems-design","status":"publish","type":"post","link":"https:\/\/euvolution.com\/open-source-convergence\/artificial-intelligence\/artificial-intelligence-assists-in-the-study-of-autonomous-vehicle-performance-in-winter-conditions-vision-systems-design.php","title":{"rendered":"Artificial intelligence assists in the study of autonomous vehicle performance in winter conditions &#8211; Vision Systems Design"},"content":{"rendered":"<p><p>In this weeks roundup from the Association for Unmanned Vehicle Systems International, which highlights some of the latest news and headlines in unmanned  vehicles and robotics, studying  autonomous vehicle operation in Canadian winters, the foundation is laid out  for ZM Interactive customers to conduct beyond-line-of-sight  drone flights, and unmanned surface vehicles conduct seabed surveys on offshore  wind farm turbines.<\/p>\n<p>Scale AI open-sources data set to help in the development  of autonomous vehicles capable of driving in wintry weather<\/p>\n<p>This week, a startup called Scale AI open-sourced Canadian Adverse  Driving Conditions (CADC), which is a data set that contains more than 56,000  images in conditions including snow created with the University of Waterloo and  the University of Toronto. <\/p>\n<p>The move is designed to help in the development of  autonomous vehicles capable of driving in wintry weather, as Scale AI claims  that CADC is the first corpora with snowy sensor samples to focus specifically  on real-world driving in snowy weather.<\/p>\n<p>Snow is hard to drive in  as many drivers are well aware.  But wintry conditions are especially hard for self-driving cars because of the  way snow affects the critical hardware and AI algorithms that power them,  explains Scale AI CEO Alexandr Wang in a blog post, via VentureBeat. <\/p>\n<p>A skilled human driver can handle the same road in all  weathers  but todays AV models cant generalize their experience in the same  way. To do so, they need much more data.<\/p>\n<p>According to Scale AI, the routes captured in CADC were  chosen based on levels of traffic and the variety of objects such as cars,  pedestrians, animals, and most importantly, snowfall. Teams of engineers used  an autonomous vehicle platform called Autonomoose to drive a Lincoln MKZ Hybrid  mounted with a suite of lidar, inertial sensors, GPS, and vision sensors  (including eight wide-angle cameras) along 12.4 miles of Waterloo roads. <\/p>\n<p>Combining human work and review with smart tools,  statistical confidence checks, and machine learning checks, Scale AIs data  annotation platform was used to label each of the resulting camera images,  7,000 lidar sweeps, and 75 scenes of 50-100 frames. The company says that the  accuracy is consistently higher than what a human or synthetic labeling  technique could achieve independently, as measured against seven different  annotation quality areas.<\/p>\n<p>For University of Waterloo professor Krzysztof Czarnecki,  his hope is that the data set will put the wider research community on equal  footing with companies that testing self-driving cars in winter conditions,  including Alphabets Waymo, Argo, and Yandex.<\/p>\n<p>We want to engage the research community to generate new  ideas and enable innovation, Czarnecki says. This is how you can solve really  hard problems, the problems that are just too big for anyone to solve on their  own.<\/p>\n<p>ZM Interactive selects Iris Automation as detect and  avoid provider for its UAS<\/p>\n<p>ZM Interactive (ZMI) has selected Iris Automation as the  detect and avoid (DAA) provider for its drones, which will allow ZMI customers  to conduct beyond visual line of sight (BVLOS) operations.<\/p>\n<p>ZMI manufactures the xFold drone, which is an industrial,  military-grade UAS that comes in various sizes and configurations. Its frame  can change between a x4 (Quad), x6 (Hexa), X8 (octo) and X12 (Dodeca)  configurations in minutes, and it has a heavy payload capability of more than  300 pounds, making the UAS ideal for a wide range of commercial, industrial,  military and emergency response applications. Some of its use cases include  aerial cinematography, 3-D Mapping and inspections, and cargo delivery.<\/p>\n<p>Having selected Iris Automation as its DAA provider, ZMI  will provide the option of equipping its UAS platforms with Iris Automations  Casia system. Described as a turnkey solution, Casia detects, tracks and  classifies other aircraft and makes informed decisions about the threat they  could potentially pose to the UAS. To avoid collisions, Casia triggers  automated maneuvers, and alerts the pilot in command of the mission.<\/p>\n<p>This collaboration between Iris Automation and ZMI allows  xFold drone customers to use their drones to their full potential, explains  Iris Automation CEO Alexander Harmsen.<\/p>\n<p>Having drones pre-equipped with the option for advanced  BVLOS capabilities is a basic requirement the industry will soon expect to see  on all drones out-of-the-box.<\/p>\n<p>Under its partnership with ZMI, Iris says that it will also  offer customers with Casia onboard regulatory support for Part 107 waiver  writing and regulatory approval processes to secure the permissions needed to  conduct their unique BVLOS operations.<\/p>\n<\/p>\n<p>XOCEAN's XO-450 USV conducts seabed surveys for Greater  Gabbard Offshore Wind Farm<\/p>\n<p>Considered a first for the offshore wind sector, XOCEANs  XO-450 USV recently conducted seabed surveys on seven of the turbines at the  Greater Gabbard Offshore Wind Farm, a joint venture between SSE Renewables and  innogy. <\/p>\n<p>To validate data collection before the vessel departed the  work locations, experts located in the United Kingdom monitored the data  collected from shore in real-time throughout the survey. <\/p>\n<p>According to XOCEAN, the survey demonstrates the highly  flexible and collaborative nature of this technology, which ultimately allows  industry experts to have direct access to real time data, from any location.<\/p>\n<p>We are constantly looking for innovative ways in which we  can operate our fleet of renewables assets, says Jeremy Williamson, SSE  Renewables Head of Operations.<\/p>\n<p>XOCEANs vessel will allow us to carry out our work in a  more efficient, and most importantly for SSE Renewables and our partners  innogy, in the safest way possible. Were really interested to see how this  sort of work can help improve our industry and look forward to working with  XOCEAN in future.<\/p>\n<p>XOCEAN says that its USVs offer a number of benefits, including  keeping operators safe as they remain onshore, efficiency with operations 24  hours a day, seven days a week, and environmental benefits with ultra-low  emission. These benefits result in significant economic savings, the company  adds.<\/p>\n<p>Our USV platform has demonstrated itself to be a safe,  reliable and low carbon solution for the collection of ocean data, says James  Ives, CEO of XOCEAN.<\/p>\n<p>We are delighted to be working with SSE and innogy on this  ground-breaking project.<\/p>\n<p>Share your vision-related news by contactingDennis Scimeca, Associate Editor, Vision Systems Design<\/p>\n<p>SUBSCRIBE TO OUR NEWSLETTERS<\/p>\n<p><!-- Auto Generated --><\/p>\n<p>Read more:<br \/>\n<a target=\"_blank\" href=\"https:\/\/www.vision-systems.com\/unmanned\/article\/14167257\/artificial-intelligence-assists-in-the-study-of-autonomous-vehicle-performance-in-winter-conditions\" title=\"Artificial intelligence assists in the study of autonomous vehicle performance in winter conditions - Vision Systems Design\" rel=\"noopener noreferrer\">Artificial intelligence assists in the study of autonomous vehicle performance in winter conditions - Vision Systems Design<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> In this weeks roundup from the Association for Unmanned Vehicle Systems International, which highlights some of the latest news and headlines in unmanned vehicles and robotics, studying autonomous vehicle operation in Canadian winters, the foundation is laid out for ZM Interactive customers to conduct beyond-line-of-sight drone flights, and unmanned surface vehicles conduct seabed surveys on offshore wind farm turbines. Scale AI open-sources data set to help in the development of autonomous vehicles capable of driving in wintry weather This week, a startup called Scale AI open-sourced Canadian Adverse Driving Conditions (CADC), which is a data set that contains more than 56,000 images in conditions including snow created with the University of Waterloo and the University of Toronto. <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[27374],"tags":[],"class_list":["post-37450","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence"],"_links":{"self":[{"href":"https:\/\/euvolution.com\/open-source-convergence\/wp-json\/wp\/v2\/posts\/37450"}],"collection":[{"href":"https:\/\/euvolution.com\/open-source-convergence\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/euvolution.com\/open-source-convergence\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/euvolution.com\/open-source-convergence\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/euvolution.com\/open-source-convergence\/wp-json\/wp\/v2\/comments?post=37450"}],"version-history":[{"count":0,"href":"https:\/\/euvolution.com\/open-source-convergence\/wp-json\/wp\/v2\/posts\/37450\/revisions"}],"wp:attachment":[{"href":"https:\/\/euvolution.com\/open-source-convergence\/wp-json\/wp\/v2\/media?parent=37450"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/euvolution.com\/open-source-convergence\/wp-json\/wp\/v2\/categories?post=37450"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/euvolution.com\/open-source-convergence\/wp-json\/wp\/v2\/tags?post=37450"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}