{"type":"ScholarlyArticle","title":"WiFi-SLAM Using Gaussian Process Latent Variable Models","authors":[{"name":"Brian Ferris","slug":"brian-ferris","given":"Brian","family":"Ferris","affiliation":""},{"name":"Dieter Fox","slug":"dieter-fox","given":"Dieter","family":"Fox","affiliation":""},{"name":"Neil D. Lawrence","slug":"neil-d-lawrence","given":"Neil D.","family":"Lawrence","affiliation":""}],"abstract":"WiFi localization, the task of determining the physical location of a mobile device from wireless signal strengths, has been shown to be an accurate method of indoor and outdoor localization and a powerful building block for location-aware applications. However, most localization techniques require a training set of signal strength readings labeled against a ground truth location map, which is prohibitive to collect and maintain as maps grow large. In this paper we propose a novel technique for solving the WiFi SLAM problem using the Gaussian Process Latent Variable Model (GP-LVM) to determine the latent-space locations of unlabeled signal strength data. We show how GP-LVM, in combination with an appropriate motion dynamics model, can be used to reconstruct a topological connectivity graph from a signal strength sequence which, in combination with the learned Gaussian Process signal strength model, can be used to perform efficient localization.","doi":null,"url":"https://ijcai.org/proceedings/2007/399","pdf":"https://ijcai.org/proceedings/2007/0399.pdf","markdown":"https://ijcai.org/proceedings/2007/399.md","bibtex":"https://ijcai.org/proceedings/2007/bibtex/399","volume":{"slug":"2007","title":"Proceedings of the Twentieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2007","url":"https://ijcai.org/proceedings/2007/","year":2007,"location":"Hyderabad, India","dates":"","editors":"Ramon López de Mántaras","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":399,"pages":{"first":2480,"last":2484},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}