Year: 2024
Type: preprint
Abstract: Lifelong localization is crucial for enabling the autonomy of service robots. In this paper, we present an overview of our past research on long-term localization and mapping, exploiting geometric priors such as floor plans and integrating textual and semantic information. Our approach was validated on challenging sequences spanning over many months, and we released open source implementations.
Source: arXiv (Cornell University)
Authors: Zimmerman, Nicky, Sodano, Matteo
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4403578060