Interactive Continual Learning Architecture for Long-Term Personalization of Home Service Robots

arXiv:2403.03462v1 Announce Type: cross
Abstract: For robots to perform assistive tasks in unstructured home environments, they must learn and reason on the semantic knowledge of the environments. Despite a resurgence in the development of semantic reasoning architectures, these methods assume that all the training data is available a priori. However, each user's environment is unique and can continue to change over time, which makes these methods unsuitable for personalized home service robots. Although research in continual learning develops methods that …

abstract architecture architectures arxiv continual cs.cv cs.lg cs.ro data development environments home interactive knowledge learn long-term personalization reason reasoning robots semantic service tasks training training data type unstructured