{"id":2406,"date":"2025-10-10T06:47:56","date_gmt":"2025-10-10T06:47:56","guid":{"rendered":"https:\/\/webroad-seisaku.com\/fujiko-test\/?page_id=2406"},"modified":"2026-05-11T00:36:51","modified_gmt":"2026-05-11T00:36:51","slug":"vehicle-mms","status":"publish","type":"page","link":"https:\/\/webroad-seisaku.com\/fujiko-test\/vehicle-mms","title":{"rendered":"SW\/HW Vehicle MMS"},"content":{"rendered":"\n

V-MMS (Vehicle Mobile Mapping System)<\/h2>\n\n\n\n

Overview<\/h3>\n\n\n\n

High-precision Mobile Mapping Systems (MMS) have been available for some time, but have not yet achieved widespread market adoption due to various factors. Kudan's V-MMS is an innovative product designed to overcome the challenges faced by conventional MMS.<\/p>\n\n\n\n

\n
\n

Conventional MMS Challenges<\/strong><\/p>\n\n\n\n

    \n
  • High quality but expensive<\/strong>
    The point cloud quality is high, but the price is expensive, which creates a high barrier to easy point cloud acquisition and generation.<\/li>\n\n\n\n
  • Difficulty integrating with other point clouds<\/strong>
    Although simple alignment is possible, point cloud acquisition is generally intended to be done with the same model of device.<\/li>\n\n\n\n
  • Difficult to use and master<\/strong>
    It requires a certain level of expertise, and it takes time to master its use.<\/li>\n<\/ul>\n<\/div>\n\n\n\n
    \n
    \"\"<\/figure>\n\n\n\n
    \"\"<\/figure>\n<\/div>\n\n\n\n
    \n

    Concept of Kudan V-MMS<\/strong><\/p>\n\n\n\n

      \n
    • Easily acquire high-quality point clouds at a low cost.
      -> Offered at up to one-tenth the price.<\/li>\n\n\n\n
    • Advanced map integration using relocalization technology refined through our robotics business.
      -> Can be integrated with 3rd party point cloud<\/li>\n\n\n\n
    • A simple, user-friendly UI that includes elements of automation.
      -> Can be used without any professional backgrounds.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n\n\n\n
      <\/div>\n\n\n\n

      Examples of Outputs<\/h3>\n\n\n\n

      We provide a wide range of high-quality outputs, not only generating point clouds but also combining them with cutting-edge AI technology.<\/p>\n\n\n\n

      \n
      \n

      Colorised 3D point cloud<\/strong><\/p>\n\n\n\n

      \n
      \n
      \"\"<\/figure>\n<\/div>\n\n\n\n
      \n
      \"\"<\/figure>\n<\/div>\n<\/div><\/div>\n<\/div>\n\n\n\n
      \n

      Semantic segmentation (3D point cloud)<\/strong><\/p>\n\n\n\n

      \n
      \n
      \"\"<\/figure>\n<\/div>\n\n\n\n
      \n
      \"\"<\/figure>\n<\/div>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n\n\n
      \n
      \n

      Georeferenced high-precision image<\/strong><\/strong><\/p>\n\n\n\n

      \n
      <\/div>\n\n\n\n
      \n
      \"\"<\/figure>\n<\/div>\n<\/div><\/div>\n<\/div>\n\n\n\n
      \n

      Example of On-Vehicle Installation<\/strong><\/p>\n\n\n\n

      \"\"<\/figure>\n<\/div>\n<\/div>\n\n\n\n
      <\/div>\n\n\n\n

      Characteristics<\/h3>\n\n\n\n
      \n
      \n

      Hardware<\/strong>:<\/strong>
      Simple configuration that can be retrofitted to existing vehicles.<\/p>\n\n\n\n

      \"\"<\/figure>\n<\/div>\n\n\n\n
      \n

      Simple UI<\/strong>:<\/strong>
      Intuitive operation with no specialized knowledge required.<\/p>\n\n\n\n

      \"\"<\/figure>\n\n\n\n
      \"\"<\/figure>\n<\/div>\n<\/div>\n\n\n\n
      \n
      \n

      Noise Filtering<\/strong>:<\/strong>
      Advanced noise filtering that integrates object recognition technology.<\/p>\n\n\n\n

      \n
      \n
      \"\"<\/figure>\n<\/div>\n\n\n\n
      \n
      \"\"<\/figure>\n<\/div>\n<\/div><\/div>\n<\/div>\n\n\n\n
      \n

      GCP Correction<\/strong>:<\/strong>
      Simple UI for ground control point (GCP) input and map-wide accuracy correction.<\/p>\n\n\n\n

      \"\"<\/figure>\n<\/div>\n<\/div>\n\n\n\n
      \n
      \n

      Map Handling<\/strong>\uff1a<\/strong>
      Advanced map integration with 3rd party point clouds is also possible.<\/p>\n\n\n\n

      \n
      \n
      \"\"<\/figure>\n<\/div>\n\n\n\n
      \n

      Blue: 3rd party
      pointcloud<\/p>\n\n\n\n

      White: Kudan
      pointcloud
      Red: Difference
       between 2
      pointclouds<\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

      \n

      Semantic Segmentation:<\/strong>
      Segmentation of objects within a point cloud using AI image recognition technology.<\/p>\n\n\n\n

      \n
      \n
      \"\"<\/figure>\n<\/div>\n\n\n\n
      \n
      \"\"<\/figure>\n<\/div>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n\n\n
      <\/div>\n\n\n\n

      Use cases<\/h3>\n\n\n\n
      \n
      \n

      Surveying<\/strong><\/p>\n\n\n\n

      \"\"<\/figure>\n<\/div>\n\n\n\n
      \n

      Disaster prevention and management<\/strong><\/p>\n\n\n\n

      \"\"<\/figure>\n<\/div>\n\n\n\n
      \n

      Next-generation applications through 3D Point Clouds x Imagery x AI<\/strong><\/p>\n\n\n\n

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

      V-MMS (Vehicle Mobile Mapping System) Overview High-precision Mobile Mapping Systems (MMS) have been available for some time, but have not yet achieved widespread market adoption due to various factors. Kudan's V-MMS is an innovative product designed to overcome the challenges faced by conventional MMS. Conventional MMS Challenges Concept of Kudan V-MMS Examples of Outputs We […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"sns_share_botton_hide":"","vkExUnit_sns_title":"","_vk_print_noindex":"","sitemap_hide":"","vkExUnit_sitemap":"","_veu_custom_css":"","veu_display_promotion_alert":"common","_exclude_from_list_pages":"","vkexunit_cta_each_option":"","vkExUnit_childPageIndex":"","vkExUnit_pageList_ancestor":"","vkExUnit_contact_enable":"","_lightning_design_setting":{"layout":"default","section_base":"default","header_trans":"default","site_body_padding":"true"},"header_top_description":"","vk_page_header_image":0,"vk_page_header_image_sp":0,"vk_page_header_subtext":"","footnotes":""},"class_list":["post-2406","page","type-page","status-publish","hentry"],"veu_head_title_object":{"title":"","add_site_title":""},"_links":{"self":[{"href":"https:\/\/webroad-seisaku.com\/fujiko-test\/wp-json\/wp\/v2\/pages\/2406","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/webroad-seisaku.com\/fujiko-test\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/webroad-seisaku.com\/fujiko-test\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/webroad-seisaku.com\/fujiko-test\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/webroad-seisaku.com\/fujiko-test\/wp-json\/wp\/v2\/comments?post=2406"}],"version-history":[{"count":7,"href":"https:\/\/webroad-seisaku.com\/fujiko-test\/wp-json\/wp\/v2\/pages\/2406\/revisions"}],"predecessor-version":[{"id":3066,"href":"https:\/\/webroad-seisaku.com\/fujiko-test\/wp-json\/wp\/v2\/pages\/2406\/revisions\/3066"}],"wp:attachment":[{"href":"https:\/\/webroad-seisaku.com\/fujiko-test\/wp-json\/wp\/v2\/media?parent=2406"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}