首页|Reports on Robotics Findings from Technical University Munich (TU Munich) Provid e New Insights (Generalized Synchronized Active Learning for Multi-agent-based D ata Selection On Mobile Robotic Systems)
Reports on Robotics Findings from Technical University Munich (TU Munich) Provid e New Insights (Generalized Synchronized Active Learning for Multi-agent-based D ata Selection On Mobile Robotic Systems)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ro botics. According to news originating from Munich, Germany, by NewsRx correspond ents, research stated, "In mobile robotics, perception in uncontrolled environme nts like autonomous driving is a central hurdle. Existing active learning framew orks can help enhance perception by efficiently selecting data samples for label ing, but they are often constrained by the necessity of full data availability i n data centers, hindering real-time, on-field adaptations." Our news journalists obtained a quote from the research from Technical Universit y Munich (TU Munich), "To address this, our work unveils a novel active learning formulation optimized for multi-robot settings. It harnesses the collaborative power of several robotic agents, considerably enhancing the data acquisition and synchronization processes." According to the news editors, the research concluded: "Experimental evidence in dicates that our approach markedly surpasses traditional active learning framewo rks by up to 2.5 percent points and 90% less data uploads, deliver ing new possibilities for advancements in the realms of mobile robotics and auto nomous systems."
MunichGermanyEuropeEmerging Techno logiesMachine LearningRoboticsRobotsTechnical University Munich (TU Muni ch)
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