Proceedings:
Book One
Volume
Issue:
Proceedings of the AAAI Conference on Artificial Intelligence, 17
Track:
SIGART/AAAI Doctoral Consortium
Downloads:
Abstract:
Our work addresses the problem of learning a set of visual landmarks for mobile robot localization. The learning framework is designed to be applicable to a wide range of environments, and allows for different approaches to computing a pose estimate. Initially, each landmark is detected using a model of visual attention and is matched to observations from other poses using principal components analysis. Attributes of the observed landmarks can be parameterized using a generic parameterization method and then evaluated in terms of their utility for pose estimation. We discuss the status of the work to date, and future directions.
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence, 17