2 papers
cs.RO2024
Learning Spatial Bimanual Action Models Based on Affordance Regions and Human Demonstrations
Björn S. Plonka, Christian Dreher, Andre Meixner +2
In this paper, we present a novel approach for learning bimanual manipulation actions from human demonstration by extracting spatial constraints between affordance regions, termed…
cs.RO2024
Incremental Learning of Humanoid Robot Behavior from Natural Interaction and Large Language Models
Leonard Bärmann, Rainer Kartmann, Fabian Peller-Konrad +3
Natural-language dialog is key for intuitive human-robot interaction. It can be used not only to express humans' intents, but also to communicate instructions for improvement if a…