{"id":32712,"date":"2026-01-21T17:02:29","date_gmt":"2026-01-21T17:02:29","guid":{"rendered":"https:\/\/lamarr-institute.org\/publication\/real-time-predictive-scheduling-for-networked-robot-control-using-digital-twins-and-openran\/"},"modified":"2026-09-17T11:25:41","modified_gmt":"2026-09-17T11:25:41","slug":"real-time-predictive-scheduling-for-networked-robot-control-using-digital-twins-and-openran","status":"publish","type":"publication","link":"https:\/\/lamarr-institute.org\/de\/publication\/real-time-predictive-scheduling-for-networked-robot-control-using-digital-twins-and-openran\/","title":{"rendered":"Real-Time Predictive Scheduling for Networked Robot Control Using Digital Twins and OpenRAN"},"content":{"rendered":"<p>Safe and efficient real-time robotics control is highly delay-sensitive. Enabling such critical applications via mobile communication networks, therefore, hinges on reliably provisioning radio resources at low latency. Here, employing the Open Radio Access Network (O-RAN) concept, networks can be built with adaptive intelligent features, such as Artificial Intelligence (AI)-based scheduling policies for optimized resource management. By harnessing the innovative concept of distributed Applications (dApps) deployed inside the Open RAN Distributed Unit (O-DU), predictive resource allocation can reliably provide low latencies for robot control at increased spectral efficiency. This work demonstrates the Key Performance Indicators (KPIs) achieved with a proposed real-time proactive scheduling dApp employing AI methods. Results are derived from a real-world testbed that integrates predictive communication with a digital twin of the two-wheeled inverted pendulum robot evoBOT, designed for intralogistics. The closed-loop locomotion control, also providing upright stability control, is performed on the mobile edge via an evolved O-RAN system hosting the proposed dApp. Relative to optimized reactive network slicing, our approach yields a 34\\% mean reduction for uplink delays. Moreover, radio resource usage is reduced by up to 47\\% compared to highly optimized reactive scheduling, exhibiting similar control performance.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Safe and efficient real-time robotics control is highly delay-sensitive. Enabling such critical applications via mobile communication networks, therefore, hinges on reliably provisioning radio resources at low latency. Here, employing the Open Radio Access Network (O-RAN) concept, networks can be built with adaptive intelligent features, such as Artificial Intelligence (AI)-based scheduling policies for optimized resource management. By harnessing the innovative concept of distributed Applications (dApps) deployed inside the Open RAN Distributed [&hellip;]<\/p>\n","protected":false},"author":14,"featured_media":0,"template":"","meta":{"_acf_changed":false,"footnotes":""},"publication-type":[32],"class_list":["post-32712","publication","type-publication","status-publish","hentry","publication-type-inproceedings"],"acf":[],"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/32712","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication"}],"about":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/types\/publication"}],"author":[{"embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/users\/14"}],"version-history":[{"count":0,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication\/32712\/revisions"}],"wp:attachment":[{"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/media?parent=32712"}],"wp:term":[{"taxonomy":"publication-type","embeddable":true,"href":"https:\/\/lamarr-institute.org\/de\/wp-json\/wp\/v2\/publication-type?post=32712"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}