{"id":560,"date":"2025-06-27T08:30:56","date_gmt":"2025-06-27T08:30:56","guid":{"rendered":"https:\/\/interplanix.com\/?page_id=560"},"modified":"2025-07-03T15:12:39","modified_gmt":"2025-07-03T15:12:39","slug":"space-traffic-ai-simulator","status":"publish","type":"page","link":"https:\/\/interplanix.com\/index.php\/space-traffic-ai-simulator\/","title":{"rendered":"Space Traffic AI Simulator"},"content":{"rendered":"\n<div style=\"max-width: 960px; margin: auto; padding: 40px; font-family: Arial, sans-serif; line-height: 1.6;\">\n\n  <h1 style=\"text-align: center; color: #003366;\">\ud83d\udef0\ufe0f Space Traffic AI Simulator<\/h1>\n\n  <p>\n    The <strong>Space Traffic AI Simulator<\/strong> provides an interactive and visual approach to understanding satellite orbits in Low Earth Orbit (LEO) using Two-Line Element (TLE) data. It enables space professionals, researchers, and enthusiasts to observe satellite dynamics over a time period, laying the foundation for predictive collision avoidance powered by artificial intelligence.\n  <\/p>\n\n  <p>\n    The tool uses orbital propagation techniques to simulate 90 minutes of motion based on real or simulated TLE data. It also introduces basic elements of SSA (Space Situational Awareness) and supports visualization needed for future AI-driven orbital traffic deconfliction systems.\n  <\/p>\n\n  <h2 style=\"margin-top: 30px; color: #003366;\">\u2705 Key Capabilities<\/h2>\n  <ul>\n    <li>\ud83d\ude80 Load and visualize real-world or sample satellite TLE data<\/li>\n    <li>\ud83e\udded Simulate orbital propagation over a 90-minute period<\/li>\n    <li>\ud83c\udf10 3D interactive orbit visualization using Plotly (pan, zoom, rotate)<\/li>\n    <li>\ud83d\udcca Extendable for reinforcement learning (AI-based maneuver planning)<\/li>\n  <\/ul>\n\n  <p>\n    This simulator is a building block for real-time orbital monitoring systems that help detect high-risk conjunctions and plan evasive maneuvers using reinforcement learning agents.\n  <\/p>\n\n  <hr style=\"margin: 50px 0;\">\n\n  <h2 style=\"text-align: center; color: #003366;\">\ud83d\udc47 Live Visualization<\/h2>\n\n  <iframe loading=\"lazy\" \n    src=\"https:\/\/rajesh-uppal.github.io\/interplanix\/space_traffic_simulation.html\" \n    width=\"100%\" \n    height=\"600\" \n    style=\"border: none; border-radius: 6px; box-shadow: 0 0 10px rgba(0,0,0,0.1);\">\n  <\/iframe>\n\n  <p style=\"text-align: center; margin-top: 20px;\">\n    \ud83d\udccd This live map updates dynamically based on the selected TLE set and offers visual insights into current satellite traffic, potential intersections, and orbital behavior.\n  <\/p>\n\n  <hr style=\"margin: 60px 0;\">\n\n  <p style=\"text-align: center; font-size: 14px; color: #666;\">\n    Built by <strong>Interplanix<\/strong> \u2014 advancing open-source tools for orbital safety and SSA.\n  <\/p>\n\n<\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>\ud83d\udef0\ufe0f Space Traffic AI Simulator The Space Traffic AI Simulator provides an interactive and visual approach to understanding satellite orbits in Low Earth Orbit (LEO) using Two-Line Element (TLE) data. It enables space professionals, researchers, and enthusiasts to observe satellite dynamics over a time period, laying the foundation for predictive collision avoidance powered by artificial [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_uag_custom_page_level_css":"","footnotes":""},"class_list":["post-560","page","type-page","status-publish","hentry"],"blocksy_meta":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"interplanix.com","author_link":"https:\/\/interplanix.com\/author\/interplanix-com\/"},"uagb_comment_info":0,"uagb_excerpt":"\ud83d\udef0\ufe0f Space Traffic AI Simulator The Space Traffic AI Simulator provides an interactive and visual approach to understanding satellite orbits in Low Earth Orbit (LEO) using Two-Line Element (TLE) data. It enables space professionals, researchers, and enthusiasts to observe satellite dynamics over a time period, laying the foundation for predictive collision avoidance powered by artificial&hellip;","_links":{"self":[{"href":"https:\/\/interplanix.com\/index.php\/wp-json\/wp\/v2\/pages\/560","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/interplanix.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/interplanix.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/interplanix.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/interplanix.com\/index.php\/wp-json\/wp\/v2\/comments?post=560"}],"version-history":[{"count":3,"href":"https:\/\/interplanix.com\/index.php\/wp-json\/wp\/v2\/pages\/560\/revisions"}],"predecessor-version":[{"id":570,"href":"https:\/\/interplanix.com\/index.php\/wp-json\/wp\/v2\/pages\/560\/revisions\/570"}],"wp:attachment":[{"href":"https:\/\/interplanix.com\/index.php\/wp-json\/wp\/v2\/media?parent=560"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}