{"id":22806,"date":"2025-10-23T13:27:45","date_gmt":"2025-10-23T13:27:45","guid":{"rendered":"https:\/\/aerospacerepository.org\/?p=22806"},"modified":"2025-10-23T13:27:46","modified_gmt":"2025-10-23T13:27:46","slug":"efficient-hypersonic-guidance-through-neural-network-based-trajectory-generation","status":"publish","type":"post","link":"https:\/\/aerospacerepository.org\/index.php\/2025\/10\/23\/efficient-hypersonic-guidance-through-neural-network-based-trajectory-generation\/","title":{"rendered":"Efficient Hypersonic Guidance Through Neural Network-Based Trajectory Generation"},"content":{"rendered":"\n<p><strong>Prince EDORH, Bruno HERISSE<\/strong><\/p>\n\n\n\n<p><strong>DOI Number: N\/A<\/strong><\/p>\n\n\n\n<p><strong>Conference number: HiSST-2025-191<\/strong><\/p>\n\n\n\n<p>Hypersonic re-entry guidance poses significant challenges due to the sensitivity of optimal trajectories to dispersions in initial conditions and vehicle dynamics. Traditionally, guidance systems rely on precomputed optimal reference trajectories to mitigate these dispersions, employing on-line tracking algorithms to track to the nominal path. However, for large dispersions in initial conditions, this approach necessitates to embark either extensive databases of representative trajectories or robust online trajectory re-planning capabilities, both of which entail high computational or storage demands. Recent approaches have explored data compression techniques\u2014such as B\u00e9zier curves or optimal<br>shooting points \u2014 to reduce the storage required for representing optimal trajectories and commands. In this paper, we demonstrate that the relationship between stored representative trajectory data and initial condition dispersions can be effectively learned and subsequently leveraged onboard. Artificial neural networks have been trained offline using a limited number of optimal trajectories within an initial dispersion box. The trained model is then used online to quickly recompute an initial reference trajectory suitable for guidance algorithms such as B\u00e9zier curves-based guidance (BCBG) or Proportional Navigation (PN). This approach enables coverage of a large dispersion box in Monte Carlo simulations while satisfying precision requirements and various path constraints significantly reducing computational and storage demands while maintaining robustness to dispersions.<\/p>\n\n\n\n<p><a href=\"https:\/\/aerospacerepository.org\/wp-content\/uploads\/2025\/10\/HISST2025_191_paper.pdf\">Read the full paper here<\/a><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p><b>Prince EDORH, Bruno HERISSE<\/b><\/p>\n<p>DOI Number: N\/A<\/p>\n<p>Conference number: HiSST-2025-191<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[993,3365,3361],"tags":[3583,3585,3586,3584],"class_list":["post-22806","post","type-post","status-publish","format-standard","hentry","category-events","category-guidance-control-systems-including-flight-mechanics-guidance-navigation-routing","category-1-hisst-2025","tag-bezier-curves","tag-optimal-guidance","tag-surrogate-modeling","tag-trajectory-generation","category-993","category-3365","category-3361","description-off"],"_links":{"self":[{"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/posts\/22806","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/comments?post=22806"}],"version-history":[{"count":1,"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/posts\/22806\/revisions"}],"predecessor-version":[{"id":22808,"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/posts\/22806\/revisions\/22808"}],"wp:attachment":[{"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/media?parent=22806"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/categories?post=22806"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aerospacerepository.org\/index.php\/wp-json\/wp\/v2\/tags?post=22806"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}