The article presents a new framework for Interactive Machine Learning (IML), aiming to incorporate human expertise into machine learning algorithms. The framework is grounded in Bayesian Optimization (BO), thus called…
Continue readingThe article ‘Making Informed Decisions: Supporting Cobot Integration Considering Business and Worker Preferences’ emphasizes on the need for effective integration of collaborative robots (cobots) in manufacturing settings. The authors propose…
Continue readingThe paper investigates the effects of human leading or following preferences on human-robot collaboration and perception of the robot. The authors propose a task planning framework that takes into account…
Continue readingThis article presents a framework for robot task planning that is adaptive to human preferences and performance. The authors focus on task allocation and scheduling in collaborative settings, aiming to…
Continue readingThe article focuses on improving human-robot collaborations, particularly in collaborative manufacturing scenarios where pre-existing data is scarce. The authors propose a model-based formulation of conditional behavior prediction that allows the…
Continue readingThe paper investigates the creation of multi-agent strategy explanations to improve human-robot collaboration. It emphasizes the increasing importance of robots’ ability to collaborate fluently with humans, especially in social, home,…
Continue readingThe study explores how participants used various methods of communication to explore a remote location with a robotic partner. These methods included spoken natural language instructions, text-based feedback, continuous 2D…
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